From f28c7585a850cdd8a6ef48ae8a41a2fafe578c27 Mon Sep 17 00:00:00 2001 From: Jerry Zhang Date: Mon, 4 May 2020 15:43:48 -0700 Subject: [PATCH 1/2] resnest14 --- .../classification/imagenet/resnest14.log | 7230 +++++++++++++++++ .../logs/classification/imagenet/resnest14.sh | 1 + 2 files changed, 7231 insertions(+) create mode 100644 gluoncv/logs/classification/imagenet/resnest14.log create mode 100644 gluoncv/logs/classification/imagenet/resnest14.sh diff --git a/gluoncv/logs/classification/imagenet/resnest14.log b/gluoncv/logs/classification/imagenet/resnest14.log new file mode 100644 index 000000000..5a6be997b --- /dev/null +++ b/gluoncv/logs/classification/imagenet/resnest14.log @@ -0,0 +1,7230 @@ +-------------------------------------------------------------------------- +WARNING: Linux kernel CMA support was requested via the +btl_vader_single_copy_mechanism MCA variable, but CMA support is +not available due to restrictive ptrace settings. + +The vader shared memory BTL will fall back on another single-copy +mechanism if one is available. This may result in lower performance. + + Local host: ip-172-31-29-212 +-------------------------------------------------------------------------- +[1,1]:Using AutoAugment +[1,3]:Using AutoAugment +[1,7]:Using AutoAugment +[1,6]:Using AutoAugment +[1,5]:Using AutoAugment +[1,0]:INFO:root:Namespace(auto_aug=True, batch_size=128, crop_ratio=0.875, data_nthreads=12, dropblock_prob=0, dtype='float32', eval_frequency=5, hard_weight=0.5, input_size=224, label_smoothing=True, last_gamma=True, log_interval=100, lr=0.05, mixup=True, mixup_alpha=0.2, mixup_off_epoch=0, model='resnest14', momentum=0.9, no_cuda=False, no_wd=True, num_epochs=270, rec_train='/home/ubuntu/data/ILSVRC2012/train.rec', rec_val='/home/ubuntu/data/ILSVRC2012/val.rec', resume_epoch=0, resume_params='', resume_states='', save_dir='params_resnest14', save_frequency=20, teacher=None, temperature=20, use_avd=False, use_pretrained=False, use_rec=True, use_sk=False, warmup_epochs=5, warmup_lr=0.0, wd=0.0001) +[1,2]:Using AutoAugment +[1,0]:Using AutoAugment +[1,4]:Using AutoAugment +[1,0]:INFO:root:ResNeSt( +[1,0]: (conv1): HybridSequential( +[1,0]: (0): Conv2D(3 -> 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) +[1,0]: (1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=32) +[1,0]: (2): Activation(relu) +[1,0]: (3): Conv2D(32 -> 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) +[1,0]: (4): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=32) +[1,0]: (5): Activation(relu) +[1,0]: (6): Conv2D(32 -> 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) +[1,0]: ) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) +[1,0]: (relu): Activation(relu) +[1,0]: (maxpool): MaxPool2D(size=(3, 3), stride=(2, 2), padding=(1, 1), ceil_mode=False, global_pool=False, pool_type=max, layout=NCHW) +[1,0]: (layer1): HybridSequential( +[1,0]: (0): Bottleneck( +[1,0]: (conv1): Conv2D(64 -> 64, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) +[1,0]: (relu1): Activation(relu) +[1,0]: (conv2): SplitAttentionConv( +[1,0]: (conv): Conv2D(32 -> 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2, bias=False) +[1,0]: (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) +[1,0]: (relu): Activation(relu) +[1,0]: (fc1): Conv2D(64 -> 32, kernel_size=(1, 1), stride=(1, 1)) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=32) +[1,0]: (relu1): Activation(relu) +[1,0]: (fc2): Conv2D(32 -> 128, kernel_size=(1, 1), stride=(1, 1)) +[1,0]: ) +[1,0]: (conv3): Conv2D(64 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) +[1,0]: (relu3): Activation(relu) +[1,0]: (downsample): HybridSequential( +[1,0]: (0): AvgPool2D(size=(1, 1), stride=(1, 1), padding=(0, 0), ceil_mode=True, global_pool=False, pool_type=avg, layout=NCHW) +[1,0]: (1): Conv2D(64 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) +[1,0]: ) +[1,0]: ) +[1,0]: ) +[1,0]: (layer2): HybridSequential( +[1,0]: (0): Bottleneck( +[1,0]: (conv1): Conv2D(256 -> 128, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) +[1,0]: (relu1): Activation(relu) +[1,0]: (conv2): SplitAttentionConv( +[1,0]: (conv): Conv2D(64 -> 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2, bias=False) +[1,0]: (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) +[1,0]: (relu): Activation(relu) +[1,0]: (fc1): Conv2D(128 -> 64, kernel_size=(1, 1), stride=(1, 1)) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=64) +[1,0]: (relu1): Activation(relu) +[1,0]: (fc2): Conv2D(64 -> 256, kernel_size=(1, 1), stride=(1, 1)) +[1,0]: ) +[1,0]: (conv3): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) +[1,0]: (avd_layer): AvgPool2D(size=(3, 3), stride=(2, 2), padding=(1, 1), ceil_mode=False, global_pool=False, pool_type=avg, layout=NCHW) +[1,0]: (relu3): Activation(relu) +[1,0]: (downsample): HybridSequential( +[1,0]: (0): AvgPool2D(size=(2, 2), stride=(2, 2), padding=(0, 0), ceil_mode=True, global_pool=False, pool_type=avg, layout=NCHW) +[1,0]: (1): Conv2D(256 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) +[1,0]: ) +[1,0]: ) +[1,0]: ) +[1,0]: (layer3): HybridSequential( +[1,0]: (0): Bottleneck( +[1,0]: (conv1): Conv2D(512 -> 256, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, mo[1,0]:mentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) +[1,0]: (relu1): Activation(relu) +[1,0]: (conv2): SplitAttentionConv( +[1,0]: (conv): Conv2D(128 -> 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2, bias=False) +[1,0]: (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) +[1,0]: (relu): Activation(relu) +[1,0]: (fc1): Conv2D(256 -> 128, kernel_size=(1, 1), stride=(1, 1)) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=128) +[1,0]: (relu1): Activation(relu) +[1,0]: (fc2): Conv2D(128 -> 512, kernel_size=(1, 1), stride=(1, 1)) +[1,0]: ) +[1,0]: (conv3): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) +[1,0]: (avd_layer): AvgPool2D(size=(3, 3), stride=(2, 2), padding=(1, 1), ceil_mode=False, global_pool=False, pool_type=avg, layout=NCHW) +[1,0]: (relu3): Activation(relu) +[1,0]: (downsample): HybridSequential( +[1,0]: (0): AvgPool2D(size=(2, 2), stride=(2, 2), padding=(0, 0), ceil_mode=True, global_pool=False, pool_type=avg, layout=NCHW) +[1,0]: (1): Conv2D(512 -> 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) +[1,0]: ) +[1,0]: ) +[1,0]: ) +[1,0]: (layer4): HybridSequential( +[1,0]: (0): Bottleneck( +[1,0]: (conv1): Conv2D(1024 -> 512, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=512) +[1,0]: (relu1): Activation(relu) +[1,0]: (conv2): SplitAttentionConv( +[1,0]: (conv): Conv2D(256 -> 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2, bias=False) +[1,0]: (bn): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=1024) +[1,0]: (relu): Activation(relu) +[1,0]: (fc1): Conv2D(512 -> 256, kernel_size=(1, 1), stride=(1, 1)) +[1,0]: (bn1): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=256) +[1,0]: (relu1): Activation(relu) +[1,0]: (fc2): Conv2D(256 -> 1024, kernel_size=(1, 1), stride=(1, 1)) +[1,0]: ) +[1,0]: (conv3): Conv2D(512 -> 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (bn3): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) +[1,0]: (avd_layer): AvgPool2D(size=(3, 3), stride=(2, 2), padding=(1, 1), ceil_mode=False, global_pool=False, pool_type=avg, layout=NCHW) +[1,0]: (relu3): Activation(relu) +[1,0]: (downsample): HybridSequential( +[1,0]: (0): AvgPool2D(size=(2, 2), stride=(2, 2), padding=(0, 0), ceil_mode=True, global_pool=False, pool_type=avg, layout=NCHW) +[1,0]: (1): Conv2D(1024 -> 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) +[1,0]: (2): BatchNorm(axis=1, eps=1e-05, momentum=0.9, fix_gamma=False, use_global_stats=False, in_channels=2048) +[1,0]: ) +[1,0]: ) +[1,0]: ) +[1,0]: (avgpool): GlobalAvgPool2D(size=(1, 1), stride=(1, 1), padding=(0, 0), ceil_mode=True, global_pool=True, pool_type=avg, layout=NCHW) +[1,0]: (flat): Flatten +[1,0]: (fc): Dense(2048 -> 1000, linear) +[1,0]:) +[ip-172-31-29-212:52930] 7 more processes have sent help message help-btl-vader.txt / cma-permission-denied +[ip-172-31-29-212:52930] Set MCA parameter "orte_base_help_aggregate" to 0 to see all help / error messages +[1,7]:[02:55:16] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,1]:[02:55:17] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,2]:[02:55:17] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,6]:[02:55:18] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,4]:[02:55:18] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,3]:[02:55:18] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,0]:[02:55:19] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,5]:[02:55:20] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,0]:INFO:root:Epoch[0] Batch[100] Loss[6.968] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[100] rmse=0.026110 lr=0.006390 +[1,0]:INFO:root:Epoch[0] Batch[200] Loss[6.902] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[200] rmse=0.025904 lr=0.012780 +[1,0]:INFO:root:Epoch[0] Batch[300] Loss[6.920] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[300] rmse=0.025836 lr=0.019169 +[1,0]:INFO:root:Epoch[0] Batch[400] Loss[6.819] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[400] rmse=0.025832 lr=0.025559 +[1,0]:INFO:root:Epoch[0] Batch[500] Loss[6.645] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[500] rmse=0.025945 lr=0.031949 +[1,0]:INFO:root:Epoch[0] Batch[600] Loss[6.698] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[600] rmse=0.025930 lr=0.038339 +[1,0]:INFO:root:Epoch[0] Batch[700] Loss[6.723] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[700] rmse=0.025995 lr=0.044728 +[1,0]:INFO:root:Epoch[0] Batch[800] Loss[6.681] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[800] rmse=0.026082 lr=0.051118 +[1,0]:INFO:root:Epoch[0] Batch[900] Loss[6.368] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[900] rmse=0.026126 lr=0.057508 +[1,0]:INFO:root:Epoch[0] Batch[1000] Loss[6.377] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[1000] rmse=0.026119 lr=0.063898 +[1,0]:INFO:root:Epoch[0] Batch[1100] Loss[6.606] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[1100] rmse=0.026145 lr=0.070288 +[1,0]:INFO:root:Epoch[0] Batch[1200] Loss[6.162] +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[1200] rmse=0.026096 lr=0.076677 +[1,0]:INFO:root:Epoch[0] Rank[0] Batch[1251] Time cost=411.25 Train-metric=0.026114 +[1,0]:INFO:root:Epoch[0] Speed: 3114.92 samples/sec +[1,0]:INFO:root:Epoch[1] Batch[100] Loss[6.538] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[100] rmse=0.026010 lr=0.086326 +[1,0]:INFO:root:Epoch[1] Batch[200] Loss[6.005] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[200] rmse=0.026021 lr=0.092716 +[1,0]:INFO:root:Epoch[1] Batch[300] Loss[6.032] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[300] rmse=0.026005 lr=0.099105 +[1,0]:INFO:root:Epoch[1] Batch[400] Loss[6.288] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[400] rmse=0.025951 lr=0.105495 +[1,0]:INFO:root:Epoch[1] Batch[500] Loss[5.896] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[500] rmse=0.025931 lr=0.111885 +[1,0]:INFO:root:Epoch[1] Batch[600] Loss[5.924] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[600] rmse=0.026036 lr=0.118275 +[1,0]:INFO:root:Epoch[1] Batch[700] Loss[5.784] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[700] rmse=0.026068 lr=0.124665 +[1,0]:INFO:root:Epoch[1] Batch[800] Loss[6.021] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[800] rmse=0.026045 lr=0.131054 +[1,0]:INFO:root:Epoch[1] Batch[900] Loss[6.072] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[900] rmse=0.026026 lr=0.137444 +[1,0]:INFO:root:Epoch[1] Batch[1000] Loss[5.878] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[1000] rmse=0.026021 lr=0.143834 +[1,0]:INFO:root:Epoch[1] Batch[1100] Loss[6.373] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[1100] rmse=0.025989 lr=0.150224 +[1,0]:INFO:root:Epoch[1] Batch[1200] Loss[6.210] +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[1200] rmse=0.025946 lr=0.156613 +[1,0]:INFO:root:Epoch[1] Rank[0] Batch[1251] Time cost=403.06 Train-metric=0.025975 +[1,0]:INFO:root:Epoch[1] Speed: 3178.23 samples/sec +[1,0]:INFO:root:Epoch[2] Batch[100] Loss[6.393] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[100] rmse=0.025684 lr=0.166262 +[1,0]:INFO:root:Epoch[2] Batch[200] Loss[5.491] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[200] rmse=0.025817 lr=0.172652 +[1,0]:INFO:root:Epoch[2] Batch[300] Loss[5.498] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[300] rmse=0.025850 lr=0.179042 +[1,0]:INFO:root:Epoch[2] Batch[400] Loss[5.816] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[400] rmse=0.025743 lr=0.185431 +[1,0]:INFO:root:Epoch[2] Batch[500] Loss[6.468] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[500] rmse=0.025642 lr=0.191821 +[1,0]:INFO:root:Epoch[2] Batch[600] Loss[5.075] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[600] rmse=0.025579 lr=0.198211 +[1,0]:INFO:root:Epoch[2] Batch[700] Loss[5.993] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[700] rmse=0.025634 lr=0.204601 +[1,0]:INFO:root:Epoch[2] Batch[800] Loss[5.910] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[800] rmse=0.025607 lr=0.210990 +[1,0]:INFO:root:Epoch[2] Batch[900] Loss[4.931] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[900] rmse=0.025564 lr=0.217380 +[1,0]:INFO:root:Epoch[2] Batch[1000] Loss[5.203] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[1000] rmse=0.025557 lr=0.223770 +[1,0]:INFO:root:Epoch[2] Batch[1100] Loss[6.421] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[1100] rmse=0.025573 lr=0.230160 +[1,0]:INFO:root:Epoch[2] Batch[1200] Loss[5.375] +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[1200] rmse=0.025520 lr=0.236550 +[1,0]:INFO:root:Epoch[2] Rank[0] Batch[1251] Time cost=399.89 Train-metric=0.025506 +[1,0]:INFO:root:Epoch[2] Speed: 3203.44 samples/sec +[1,0]:INFO:root:Epoch[3] Batch[100] Loss[4.938] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[100] rmse=0.025412 lr=0.246198 +[1,0]:INFO:root:Epoch[3] Batch[200] Loss[4.823] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[200] rmse=0.025167 lr=0.252588 +[1,0]:INFO:root:Epoch[3] Batch[300] Loss[4.837] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[300] rmse=0.025393 lr=0.258978 +[1,0]:INFO:root:Epoch[3] Batch[400] Loss[5.892] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[400] rmse=0.025473 lr=0.265367 +[1,0]:INFO:root:Epoch[3] Batch[500] Loss[6.228] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[500] rmse=0.025425 lr=0.271757 +[1,0]:INFO:root:Epoch[3] Batch[600] Loss[4.889] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[600] rmse=0.025333 lr=0.278147 +[1,0]:INFO:root:Epoch[3] Batch[700] Loss[5.523] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[700] rmse=0.025333 lr=0.284537 +[1,0]:INFO:root:Epoch[3] Batch[800] Loss[4.585] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[800] rmse=0.025308 lr=0.290927 +[1,0]:INFO:root:Epoch[3] Batch[900] Loss[4.672] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[900] rmse=0.025262 lr=0.297316 +[1,0]:INFO:root:Epoch[3] Batch[1000] Loss[4.370] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[1000] rmse=0.025265 lr=0.303706 +[1,0]:INFO:root:Epoch[3] Batch[1100] Loss[4.562] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[1100] rmse=0.025291 lr=0.310096 +[1,0]:INFO:root:Epoch[3] Batch[1200] Loss[4.394] +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[1200] rmse=0.025231 lr=0.316486 +[1,0]:INFO:root:Epoch[3] Rank[0] Batch[1251] Time cost=402.00 Train-metric=0.025214 +[1,0]:INFO:root:Epoch[3] Speed: 3186.64 samples/sec +[1,0]:INFO:root:Epoch[4] Batch[100] Loss[5.590] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[100] rmse=0.024661 lr=0.326134 +[1,0]:INFO:root:Epoch[4] Batch[200] Loss[4.566] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[200] rmse=0.024546 lr=0.332524 +[1,0]:INFO:root:Epoch[4] Batch[300] Loss[4.503] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[300] rmse=0.024636 lr=0.338914 +[1,0]:INFO:root:Epoch[4] Batch[400] Loss[4.048] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[400] rmse=0.024755 lr=0.345304 +[1,0]:INFO:root:Epoch[4] Batch[500] Loss[4.986] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[500] rmse=0.024727 lr=0.351693 +[1,0]:INFO:root:Epoch[4] Batch[600] Loss[4.287] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[600] rmse=0.024665 lr=0.358083 +[1,0]:INFO:root:Epoch[4] Batch[700] Loss[4.859] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[700] rmse=0.024630 lr=0.364473 +[1,0]:INFO:root:Epoch[4] Batch[800] Loss[4.753] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[800] rmse=0.024636 lr=0.370863 +[1,0]:INFO:root:Epoch[4] Batch[900] Loss[3.926] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[900] rmse=0.024622 lr=0.377252 +[1,0]:INFO:root:Epoch[4] Batch[1000] Loss[4.337] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[1000] rmse=0.024565 lr=0.383642 +[1,0]:INFO:root:Epoch[4] Batch[1100] Loss[5.897] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[1100] rmse=0.024542 lr=0.390032 +[1,0]:INFO:root:Epoch[4] Batch[1200] Loss[4.200] +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[1200] rmse=0.024544 lr=0.396422 +[1,0]:INFO:root:Epoch[4] Rank[0] Batch[1251] Time cost=400.81 Train-metric=0.024516 +[1,0]:INFO:root:Epoch[4] Speed: 3196.10 samples/sec +[1,1]:[03:28:57] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,0]:[03:28:57] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,6]:[03:28:57] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,4]:[03:28:57] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,2]:[03:28:57] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,7]:[03:28:58] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,3]:[03:28:58] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,5]:[03:28:58] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable) +[1,0]:INFO:root:Epoch[4] Rank[0] Validation-accuracy=0.329120 Validation-top_k_accuracy_5=0.591300 +[1,0]:INFO:root:Epoch[5] Batch[100] Loss[6.020] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[100] rmse=0.023842 lr=0.400000 +[1,0]:INFO:root:Epoch[5] Batch[200] Loss[4.476] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[200] rmse=0.023963 lr=0.400000 +[1,0]:INFO:root:Epoch[5] Batch[300] Loss[5.560] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[300] rmse=0.023967 lr=0.399999 +[1,0]:INFO:root:Epoch[5] Batch[400] Loss[5.731] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[400] rmse=0.024017 lr=0.399999 +[1,0]:INFO:root:Epoch[5] Batch[500] Loss[4.411] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[500] rmse=0.024053 lr=0.399998 +[1,0]:INFO:root:Epoch[5] Batch[600] Loss[3.651] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[600] rmse=0.024110 lr=0.399997 +[1,0]:INFO:root:Epoch[5] Batch[700] Loss[4.031] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[700] rmse=0.024078 lr=0.399996 +[1,0]:INFO:root:Epoch[5] Batch[800] Loss[3.611] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[800] rmse=0.024064 lr=0.399994 +[1,0]:INFO:root:Epoch[5] Batch[900] Loss[3.908] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[900] rmse=0.024084 lr=0.399993 +[1,0]:INFO:root:Epoch[5] Batch[1000] Loss[4.317] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[1000] rmse=0.024048 lr=0.399991 +[1,0]:INFO:root:Epoch[5] Batch[1100] Loss[4.801] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[1100] rmse=0.024017 lr=0.399989 +[1,0]:INFO:root:Epoch[5] Batch[1200] Loss[4.117] +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[1200] rmse=0.024014 lr=0.399987 +[1,0]:INFO:root:Epoch[5] Rank[0] Batch[1251] Time cost=396.90 Train-metric=0.024009 +[1,0]:INFO:root:Epoch[5] Speed: 3227.59 samples/sec +[1,0]:INFO:root:Epoch[6] Batch[100] Loss[5.530] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[100] rmse=0.023413 lr=0.399984 +[1,0]:INFO:root:Epoch[6] Batch[200] Loss[3.681] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[200] rmse=0.023487 lr=0.399981 +[1,0]:INFO:root:Epoch[6] Batch[300] Loss[5.505] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[300] rmse=0.023505 lr=0.399979 +[1,0]:INFO:root:Epoch[6] Batch[400] Loss[5.287] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[400] rmse=0.023518 lr=0.399976 +[1,0]:INFO:root:Epoch[6] Batch[500] Loss[5.637] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[500] rmse=0.023517 lr=0.399973 +[1,0]:INFO:root:Epoch[6] Batch[600] Loss[3.670] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[600] rmse=0.023561 lr=0.399969 +[1,0]:INFO:root:Epoch[6] Batch[700] Loss[4.074] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[700] rmse=0.023520 lr=0.399966 +[1,0]:INFO:root:Epoch[6] Batch[800] Loss[3.888] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[800] rmse=0.023505 lr=0.399962 +[1,0]:INFO:root:Epoch[6] Batch[900] Loss[5.590] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[900] rmse=0.023511 lr=0.399959 +[1,0]:INFO:root:Epoch[6] Batch[1000] Loss[4.002] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[1000] rmse=0.023506 lr=0.399955 +[1,0]:INFO:root:Epoch[6] Batch[1100] Loss[3.459] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[1100] rmse=0.023486 lr=0.399951 +[1,0]:INFO:root:Epoch[6] Batch[1200] Loss[3.580] +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[1200] rmse=0.023465 lr=0.399946 +[1,0]:INFO:root:Epoch[6] Rank[0] Batch[1251] Time cost=401.24 Train-metric=0.023467 +[1,0]:INFO:root:Epoch[6] Speed: 3192.67 samples/sec +[1,0]:INFO:root:Epoch[7] Batch[100] Loss[5.722] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[100] rmse=0.023108 lr=0.399940 +[1,0]:INFO:root:Epoch[7] Batch[200] Loss[3.651] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[200] rmse=0.023077 lr=0.399935 +[1,0]:INFO:root:Epoch[7] Batch[300] Loss[5.294] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[300] rmse=0.023188 lr=0.399930 +[1,0]:INFO:root:Epoch[7] Batch[400] Loss[3.546] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[400] rmse=0.023169 lr=0.399925 +[1,0]:INFO:root:Epoch[7] Batch[500] Loss[3.698] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[500] rmse=0.023181 lr=0.399919 +[1,0]:INFO:root:Epoch[7] Batch[600] Loss[4.370] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[600] rmse=0.023200 lr=0.399914 +[1,0]:INFO:root:Epoch[7] Batch[700] Loss[3.864] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[700] rmse=0.023206 lr=0.399908 +[1,0]:INFO:root:Epoch[7] Batch[800] Loss[5.142] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[800] rmse=0.023172 lr=0.399903 +[1,0]:INFO:root:Epoch[7] Batch[900] Loss[4.452] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[900] rmse=0.023170 lr=0.399897 +[1,0]:INFO:root:Epoch[7] Batch[1000] Loss[3.645] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[1000] rmse=0.023207 lr=0.399890 +[1,0]:INFO:root:Epoch[7] Batch[1100] Loss[3.806] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[1100] rmse=0.023203 lr=0.399884 +[1,0]:INFO:root:Epoch[7] Batch[1200] Loss[3.898] +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[1200] rmse=0.023223 lr=0.399877 +[1,0]:INFO:root:Epoch[7] Rank[0] Batch[1251] Time cost=402.08 Train-metric=0.023212 +[1,0]:INFO:root:Epoch[7] Speed: 3186.02 samples/sec +[1,0]:INFO:root:Epoch[8] Batch[100] Loss[3.634] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[100] rmse=0.022877 lr=0.399867 +[1,0]:INFO:root:Epoch[8] Batch[200] Loss[3.400] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[200] rmse=0.022901 lr=0.399860 +[1,0]:INFO:root:Epoch[8] Batch[300] Loss[4.747] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[300] rmse=0.022917 lr=0.399853 +[1,0]:INFO:root:Epoch[8] Batch[400] Loss[5.370] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[400] rmse=0.022890 lr=0.399846 +[1,0]:INFO:root:Epoch[8] Batch[500] Loss[3.378] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[500] rmse=0.022935 lr=0.399838 +[1,0]:INFO:root:Epoch[8] Batch[600] Loss[5.494] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[600] rmse=0.022949 lr=0.399831 +[1,0]:INFO:root:Epoch[8] Batch[700] Loss[4.168] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[700] rmse=0.022956 lr=0.399823 +[1,0]:INFO:root:Epoch[8] Batch[800] Loss[4.942] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[800] rmse=0.022968 lr=0.399815 +[1,0]:INFO:root:Epoch[8] Batch[900] Loss[3.396] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[900] rmse=0.022944 lr=0.399806 +[1,0]:INFO:root:Epoch[8] Batch[1000] Loss[3.228] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[1000] rmse=0.022935 lr=0.399798 +[1,0]:INFO:root:Epoch[8] Batch[1100] Loss[3.025] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[1100] rmse=0.022899 lr=0.399789 +[1,0]:INFO:root:Epoch[8] Batch[1200] Loss[3.342] +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[1200] rmse=0.022874 lr=0.399781 +[1,0]:INFO:root:Epoch[8] Rank[0] Batch[1251] Time cost=399.20 Train-metric=0.022872 +[1,0]:INFO:root:Epoch[8] Speed: 3208.99 samples/sec +[1,0]:INFO:root:Epoch[9] Batch[100] Loss[3.327] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[100] rmse=0.022718 lr=0.399767 +[1,0]:INFO:root:Epoch[9] Batch[200] Loss[4.662] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[200] rmse=0.022743 lr=0.399758 +[1,0]:INFO:root:Epoch[9] Batch[300] Loss[5.136] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[300] rmse=0.022730 lr=0.399748 +[1,0]:INFO:root:Epoch[9] Batch[400] Loss[3.182] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[400] rmse=0.022725 lr=0.399739 +[1,0]:INFO:root:Epoch[9] Batch[500] Loss[5.391] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[500] rmse=0.022673 lr=0.399729 +[1,0]:INFO:root:Epoch[9] Batch[600] Loss[4.219] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[600] rmse=0.022653 lr=0.399719 +[1,0]:INFO:root:Epoch[9] Batch[700] Loss[5.428] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[700] rmse=0.022639 lr=0.399709 +[1,0]:INFO:root:Epoch[9] Batch[800] Loss[4.167] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[800] rmse=0.022641 lr=0.399699 +[1,0]:INFO:root:Epoch[9] Batch[900] Loss[3.790] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[900] rmse=0.022647 lr=0.399688 +[1,0]:INFO:root:Epoch[9] Batch[1000] Loss[4.589] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[1000] rmse=0.022653 lr=0.399677 +[1,0]:INFO:root:Epoch[9] Batch[1100] Loss[5.346] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[1100] rmse=0.022666 lr=0.399667 +[1,0]:INFO:root:Epoch[9] Batch[1200] Loss[3.867] +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[1200] rmse=0.022685 lr=0.399656 +[1,0]:INFO:root:Epoch[9] Rank[0] Batch[1251] Time cost=398.21 Train-metric=0.022700 +[1,0]:INFO:root:Epoch[9] Speed: 3216.93 samples/sec +[1,0]:INFO:root:Epoch[9] Rank[0] Validation-accuracy=0.477440 Validation-top_k_accuracy_5=0.736700 +[1,0]:INFO:root:Epoch[10] Batch[100] Loss[3.537] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[100] rmse=0.022510 lr=0.399639 +[1,0]:INFO:root:Epoch[10] Batch[200] Loss[3.451] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[200] rmse=0.022540 lr=0.399627 +[1,0]:INFO:root:Epoch[10] Batch[300] Loss[3.211] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[300] rmse=0.022558 lr=0.399615 +[1,0]:INFO:root:Epoch[10] Batch[400] Loss[3.461] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[400] rmse=0.022615 lr=0.399604 +[1,0]:INFO:root:Epoch[10] Batch[500] Loss[3.595] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[500] rmse=0.022633 lr=0.399592 +[1,0]:INFO:root:Epoch[10] Batch[600] Loss[4.230] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[600] rmse=0.022666 lr=0.399579 +[1,0]:INFO:root:Epoch[10] Batch[700] Loss[3.641] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[700] rmse=0.022649 lr=0.399567 +[1,0]:INFO:root:Epoch[10] Batch[800] Loss[3.503] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[800] rmse=0.022657 lr=0.399555 +[1,0]:INFO:root:Epoch[10] Batch[900] Loss[3.414] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[900] rmse=0.022651 lr=0.399542 +[1,0]:INFO:root:Epoch[10] Batch[1000] Loss[3.552] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[1000] rmse=0.022616 lr=0.399529 +[1,0]:INFO:root:Epoch[10] Batch[1100] Loss[3.272] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[1100] rmse=0.022630 lr=0.399516 +[1,0]:INFO:root:Epoch[10] Batch[1200] Loss[5.053] +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[1200] rmse=0.022605 lr=0.399503 +[1,0]:INFO:root:Epoch[10] Rank[0] Batch[1251] Time cost=401.45 Train-metric=0.022596 +[1,0]:INFO:root:Epoch[10] Speed: 3190.99 samples/sec +[1,0]:INFO:root:Epoch[11] Batch[100] Loss[3.316] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[100] rmse=0.022474 lr=0.399482 +[1,0]:INFO:root:Epoch[11] Batch[200] Loss[3.661] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[200] rmse=0.022433 lr=0.399469 +[1,0]:INFO:root:Epoch[11] Batch[300] Loss[3.185] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[300] rmse=0.022512 lr=0.399455 +[1,0]:INFO:root:Epoch[11] Batch[400] Loss[3.373] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[400] rmse=0.022498 lr=0.399441 +[1,0]:INFO:root:Epoch[11] Batch[500] Loss[3.382] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[500] rmse=0.022454 lr=0.399426 +[1,0]:INFO:root:Epoch[11] Batch[600] Loss[3.227] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[600] rmse=0.022425 lr=0.399412 +[1,0]:INFO:root:Epoch[11] Batch[700] Loss[5.718] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[700] rmse=0.022460 lr=0.399397 +[1,0]:INFO:root:Epoch[11] Batch[800] Loss[3.314] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[800] rmse=0.022441 lr=0.399383 +[1,0]:INFO:root:Epoch[11] Batch[900] Loss[3.478] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[900] rmse=0.022465 lr=0.399368 +[1,0]:INFO:root:Epoch[11] Batch[1000] Loss[3.298] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[1000] rmse=0.022444 lr=0.399352 +[1,0]:INFO:root:Epoch[11] Batch[1100] Loss[3.302] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[1100] rmse=0.022459 lr=0.399337 +[1,0]:INFO:root:Epoch[11] Batch[1200] Loss[5.339] +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[1200] rmse=0.022443 lr=0.399322 +[1,0]:INFO:root:Epoch[11] Rank[0] Batch[1251] Time cost=398.20 Train-metric=0.022444 +[1,0]:INFO:root:Epoch[11] Speed: 3217.05 samples/sec +[1,0]:INFO:root:Epoch[12] Batch[100] Loss[3.303] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[100] rmse=0.022407 lr=0.399298 +[1,0]:INFO:root:Epoch[12] Batch[200] Loss[3.812] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[200] rmse=0.022429 lr=0.399282 +[1,0]:INFO:root:Epoch[12] Batch[300] Loss[3.042] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[300] rmse=0.022403 lr=0.399266 +[1,0]:INFO:root:Epoch[12] Batch[400] Loss[3.392] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[400] rmse=0.022333 lr=0.399249 +[1,0]:INFO:root:Epoch[12] Batch[500] Loss[3.049] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[500] rmse=0.022420 lr=0.399233 +[1,0]:INFO:root:Epoch[12] Batch[600] Loss[3.536] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[600] rmse=0.022398 lr=0.399216 +[1,0]:INFO:root:Epoch[12] Batch[700] Loss[3.481] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[700] rmse=0.022381 lr=0.399200 +[1,0]:INFO:root:Epoch[12] Batch[800] Loss[3.579] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[800] rmse=0.022397 lr=0.399182 +[1,0]:INFO:root:Epoch[12] Batch[900] Loss[5.378] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[900] rmse=0.022395 lr=0.399165 +[1,0]:INFO:root:Epoch[12] Batch[1000] Loss[3.516] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[1000] rmse=0.022421 lr=0.399148 +[1,0]:INFO:root:Epoch[12] Batch[1100] Loss[3.380] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[1100] rmse=0.022440 lr=0.399130 +[1,0]:INFO:root:Epoch[12] Batch[1200] Loss[3.275] +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[1200] rmse=0.022440 lr=0.399113 +[1,0]:INFO:root:Epoch[12] Rank[0] Batch[1251] Time cost=398.92 Train-metric=0.022427 +[1,0]:INFO:root:Epoch[12] Speed: 3211.23 samples/sec +[1,0]:INFO:root:Epoch[13] Batch[100] Loss[5.545] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[100] rmse=0.022518 lr=0.399086 +[1,0]:INFO:root:Epoch[13] Batch[200] Loss[3.106] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[200] rmse=0.022432 lr=0.399067 +[1,0]:INFO:root:Epoch[13] Batch[300] Loss[4.162] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[300] rmse=0.022425 lr=0.399049 +[1,0]:INFO:root:Epoch[13] Batch[400] Loss[3.275] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[400] rmse=0.022408 lr=0.399030 +[1,0]:INFO:root:Epoch[13] Batch[500] Loss[3.476] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[500] rmse=0.022400 lr=0.399012 +[1,0]:INFO:root:Epoch[13] Batch[600] Loss[3.433] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[600] rmse=0.022388 lr=0.398993 +[1,0]:INFO:root:Epoch[13] Batch[700] Loss[5.330] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[700] rmse=0.022357 lr=0.398974 +[1,0]:INFO:root:Epoch[13] Batch[800] Loss[3.449] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[800] rmse=0.022392 lr=0.398955 +[1,0]:INFO:root:Epoch[13] Batch[900] Loss[4.113] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[900] rmse=0.022427 lr=0.398935 +[1,0]:INFO:root:Epoch[13] Batch[1000] Loss[5.247] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[1000] rmse=0.022413 lr=0.398916 +[1,0]:INFO:root:Epoch[13] Batch[1100] Loss[4.209] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[1100] rmse=0.022366 lr=0.398896 +[1,0]:INFO:root:Epoch[13] Batch[1200] Loss[3.249] +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[1200] rmse=0.022372 lr=0.398876 +[1,0]:INFO:root:Epoch[13] Rank[0] Batch[1251] Time cost=399.78 Train-metric=0.022372 +[1,0]:INFO:root:Epoch[13] Speed: 3204.29 samples/sec +[1,0]:INFO:root:Epoch[14] Batch[100] Loss[3.286] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[100] rmse=0.022107 lr=0.398845 +[1,0]:INFO:root:Epoch[14] Batch[200] Loss[3.825] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[200] rmse=0.022128 lr=0.398825 +[1,0]:INFO:root:Epoch[14] Batch[300] Loss[3.802] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[300] rmse=0.022189 lr=0.398804 +[1,0]:INFO:root:Epoch[14] Batch[400] Loss[4.039] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[400] rmse=0.022144 lr=0.398784 +[1,0]:INFO:root:Epoch[14] Batch[500] Loss[3.356] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[500] rmse=0.022214 lr=0.398763 +[1,0]:INFO:root:Epoch[14] Batch[600] Loss[3.274] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[600] rmse=0.022236 lr=0.398741 +[1,0]:INFO:root:Epoch[14] Batch[700] Loss[3.259] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[700] rmse=0.022243 lr=0.398720 +[1,0]:INFO:root:Epoch[14] Batch[800] Loss[3.648] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[800] rmse=0.022238 lr=0.398699 +[1,0]:INFO:root:Epoch[14] Batch[900] Loss[3.723] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[900] rmse=0.022239 lr=0.398677 +[1,0]:INFO:root:Epoch[14] Batch[1000] Loss[5.552] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[1000] rmse=0.022243 lr=0.398655 +[1,0]:INFO:root:Epoch[14] Batch[1100] Loss[3.233] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[1100] rmse=0.022212 lr=0.398633 +[1,0]:INFO:root:Epoch[14] Batch[1200] Loss[5.406] +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[1200] rmse=0.022197 lr=0.398611 +[1,0]:INFO:root:Epoch[14] Rank[0] Batch[1251] Time cost=399.10 Train-metric=0.022203 +[1,0]:INFO:root:Epoch[14] Speed: 3209.79 samples/sec +[1,0]:INFO:root:Epoch[14] Rank[0] Validation-accuracy=0.515760 Validation-top_k_accuracy_5=0.768100 +[1,0]:INFO:root:Epoch[15] Batch[100] Loss[3.201] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[100] rmse=0.022317 lr=0.398577 +[1,0]:INFO:root:Epoch[15] Batch[200] Loss[3.376] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[200] rmse=0.022214 lr=0.398554 +[1,0]:INFO:root:Epoch[15] Batch[300] Loss[3.470] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[300] rmse=0.022243 lr=0.398532 +[1,0]:INFO:root:Epoch[15] Batch[400] Loss[3.489] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[400] rmse=0.022248 lr=0.398509 +[1,0]:INFO:root:Epoch[15] Batch[500] Loss[3.095] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[500] rmse=0.022209 lr=0.398485 +[1,0]:INFO:root:Epoch[15] Batch[600] Loss[4.500] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[600] rmse=0.022174 lr=0.398462 +[1,0]:INFO:root:Epoch[15] Batch[700] Loss[3.170] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[700] rmse=0.022161 lr=0.398439 +[1,0]:INFO:root:Epoch[15] Batch[800] Loss[3.654] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[800] rmse=0.022142 lr=0.398415 +[1,0]:INFO:root:Epoch[15] Batch[900] Loss[3.215] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[900] rmse=0.022121 lr=0.398391 +[1,0]:INFO:root:Epoch[15] Batch[1000] Loss[3.682] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[1000] rmse=0.022135 lr=0.398367 +[1,0]:INFO:root:Epoch[15] Batch[1100] Loss[5.445] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[1100] rmse=0.022123 lr=0.398343 +[1,0]:INFO:root:Epoch[15] Batch[1200] Loss[3.763] +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[1200] rmse=0.022127 lr=0.398318 +[1,0]:INFO:root:Epoch[15] Rank[0] Batch[1251] Time cost=401.09 Train-metric=0.022139 +[1,0]:INFO:root:Epoch[15] Speed: 3193.85 samples/sec +[1,0]:INFO:root:Epoch[16] Batch[100] Loss[3.150] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[100] rmse=0.022021 lr=0.398281 +[1,0]:INFO:root:Epoch[16] Batch[200] Loss[3.884] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[200] rmse=0.021990 lr=0.398256 +[1,0]:INFO:root:Epoch[16] Batch[300] Loss[5.601] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[300] rmse=0.022036 lr=0.398231 +[1,0]:INFO:root:Epoch[16] Batch[400] Loss[3.017] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[400] rmse=0.022083 lr=0.398206 +[1,0]:INFO:root:Epoch[16] Batch[500] Loss[4.853] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[500] rmse=0.022101 lr=0.398181 +[1,0]:INFO:root:Epoch[16] Batch[600] Loss[3.438] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[600] rmse=0.022071 lr=0.398155 +[1,0]:INFO:root:Epoch[16] Batch[700] Loss[3.504] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[700] rmse=0.022116 lr=0.398129 +[1,0]:INFO:root:Epoch[16] Batch[800] Loss[4.341] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[800] rmse=0.022123 lr=0.398103 +[1,0]:INFO:root:Epoch[16] Batch[900] Loss[3.437] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[900] rmse=0.022145 lr=0.398077 +[1,0]:INFO:root:Epoch[16] Batch[1000] Loss[5.461] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[1000] rmse=0.022107 lr=0.398051 +[1,0]:INFO:root:Epoch[16] Batch[1100] Loss[3.206] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[1100] rmse=0.022097 lr=0.398024 +[1,0]:INFO:root:Epoch[16] Batch[1200] Loss[3.420] +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[1200] rmse=0.022095 lr=0.397998 +[1,0]:INFO:root:Epoch[16] Rank[0] Batch[1251] Time cost=400.70 Train-metric=0.022101 +[1,0]:INFO:root:Epoch[16] Speed: 3196.96 samples/sec +[1,0]:INFO:root:Epoch[17] Batch[100] Loss[3.242] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[100] rmse=0.021988 lr=0.397957 +[1,0]:INFO:root:Epoch[17] Batch[200] Loss[3.223] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[200] rmse=0.022069 lr=0.397930 +[1,0]:INFO:root:Epoch[17] Batch[300] Loss[4.792] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[300] rmse=0.022083 lr=0.397903 +[1,0]:INFO:root:Epoch[17] Batch[400] Loss[4.180] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[400] rmse=0.022067 lr=0.397875 +[1,0]:INFO:root:Epoch[17] Batch[500] Loss[4.909] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[500] rmse=0.022020 lr=0.397848 +[1,0]:INFO:root:Epoch[17] Batch[600] Loss[3.771] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[600] rmse=0.021950 lr=0.397820 +[1,0]:INFO:root:Epoch[17] Batch[700] Loss[3.207] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[700] rmse=0.021988 lr=0.397792 +[1,0]:INFO:root:Epoch[17] Batch[800] Loss[5.239] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[800] rmse=0.022004 lr=0.397764 +[1,0]:INFO:root:Epoch[17] Batch[900] Loss[3.770] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[900] rmse=0.021979 lr=0.397736 +[1,0]:INFO:root:Epoch[17] Batch[1000] Loss[3.259] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[1000] rmse=0.021994 lr=0.397707 +[1,0]:INFO:root:Epoch[17] Batch[1100] Loss[3.649] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[1100] rmse=0.021984 lr=0.397678 +[1,0]:INFO:root:Epoch[17] Batch[1200] Loss[3.263] +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[1200] rmse=0.021987 lr=0.397650 +[1,0]:INFO:root:Epoch[17] Rank[0] Batch[1251] Time cost=399.92 Train-metric=0.022010 +[1,0]:INFO:root:Epoch[17] Speed: 3203.17 samples/sec +[1,0]:INFO:root:Epoch[18] Batch[100] Loss[3.043] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[100] rmse=0.021863 lr=0.397606 +[1,0]:INFO:root:Epoch[18] Batch[200] Loss[3.053] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[200] rmse=0.022005 lr=0.397576 +[1,0]:INFO:root:Epoch[18] Batch[300] Loss[2.985] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[300] rmse=0.021939 lr=0.397547 +[1,0]:INFO:root:Epoch[18] Batch[400] Loss[4.045] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[400] rmse=0.021948 lr=0.397517 +[1,0]:INFO:root:Epoch[18] Batch[500] Loss[5.039] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[500] rmse=0.021975 lr=0.397487 +[1,0]:INFO:root:Epoch[18] Batch[600] Loss[2.967] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[600] rmse=0.021975 lr=0.397457 +[1,0]:INFO:root:Epoch[18] Batch[700] Loss[3.036] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[700] rmse=0.021987 lr=0.397427 +[1,0]:INFO:root:Epoch[18] Batch[800] Loss[3.749] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[800] rmse=0.021974 lr=0.397397 +[1,0]:INFO:root:Epoch[18] Batch[900] Loss[3.229] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[900] rmse=0.021985 lr=0.397366 +[1,0]:INFO:root:Epoch[18] Batch[1000] Loss[5.431] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[1000] rmse=0.022002 lr=0.397336 +[1,0]:INFO:root:Epoch[18] Batch[1100] Loss[3.071] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[1100] rmse=0.022003 lr=0.397305 +[1,0]:INFO:root:Epoch[18] Batch[1200] Loss[4.766] +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[1200] rmse=0.021982 lr=0.397274 +[1,0]:INFO:root:Epoch[18] Rank[0] Batch[1251] Time cost=398.49 Train-metric=0.021985 +[1,0]:INFO:root:Epoch[18] Speed: 3214.67 samples/sec +[1,0]:INFO:root:Epoch[19] Batch[100] Loss[4.358] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[100] rmse=0.021834 lr=0.397226 +[1,0]:INFO:root:Epoch[19] Batch[200] Loss[3.482] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[200] rmse=0.021800 lr=0.397195 +[1,0]:INFO:root:Epoch[19] Batch[300] Loss[5.413] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[300] rmse=0.021915 lr=0.397163 +[1,0]:INFO:root:Epoch[19] Batch[400] Loss[3.350] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[400] rmse=0.021878 lr=0.397131 +[1,0]:INFO:root:Epoch[19] Batch[500] Loss[3.488] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[500] rmse=0.021988 lr=0.397099 +[1,0]:INFO:root:Epoch[19] Batch[600] Loss[4.054] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[600] rmse=0.021979 lr=0.397067 +[1,0]:INFO:root:Epoch[19] Batch[700] Loss[4.175] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[700] rmse=0.021950 lr=0.397035 +[1,0]:INFO:root:Epoch[19] Batch[800] Loss[5.061] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[800] rmse=0.021959 lr=0.397002 +[1,0]:INFO:root:Epoch[19] Batch[900] Loss[3.687] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[900] rmse=0.021938 lr=0.396969 +[1,0]:INFO:root:Epoch[19] Batch[1000] Loss[4.217] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[1000] rmse=0.021934 lr=0.396936 +[1,0]:INFO:root:Epoch[19] Batch[1100] Loss[3.307] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[1100] rmse=0.021942 lr=0.396903 +[1,0]:INFO:root:Epoch[19] Batch[1200] Loss[5.301] +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[1200] rmse=0.021950 lr=0.396870 +[1,0]:INFO:root:Epoch[19] Rank[0] Batch[1251] Time cost=398.56 Train-metric=0.021955 +[1,0]:INFO:root:Epoch[19] Speed: 3214.15 samples/sec +[1,0]:INFO:root:Epoch[19] Rank[0] Validation-accuracy=0.520360 Validation-top_k_accuracy_5=0.771700 +[1,0]:INFO:root:Epoch[20] Batch[100] Loss[5.320] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[100] rmse=0.021871 lr=0.396819 +[1,0]:INFO:root:Epoch[20] Batch[200] Loss[4.256] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[200] rmse=0.021810 lr=0.396786 +[1,0]:INFO:root:Epoch[20] Batch[300] Loss[3.095] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[300] rmse=0.021807 lr=0.396752 +[1,0]:INFO:root:Epoch[20] Batch[400] Loss[4.537] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[400] rmse=0.021855 lr=0.396718 +[1,0]:INFO:root:Epoch[20] Batch[500] Loss[3.472] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[500] rmse=0.021861 lr=0.396683 +[1,0]:INFO:root:Epoch[20] Batch[600] Loss[3.335] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[600] rmse=0.021881 lr=0.396649 +[1,0]:INFO:root:Epoch[20] Batch[700] Loss[3.083] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[700] rmse=0.021902 lr=0.396614 +[1,0]:INFO:root:Epoch[20] Batch[800] Loss[2.994] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[800] rmse=0.021921 lr=0.396579 +[1,0]:INFO:root:Epoch[20] Batch[900] Loss[3.718] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[900] rmse=0.021925 lr=0.396544 +[1,0]:INFO:root:Epoch[20] Batch[1000] Loss[5.136] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[1000] rmse=0.021916 lr=0.396509 +[1,0]:INFO:root:Epoch[20] Batch[1100] Loss[2.796] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[1100] rmse=0.021905 lr=0.396474 +[1,0]:INFO:root:Epoch[20] Batch[1200] Loss[3.127] +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[1200] rmse=0.021907 lr=0.396439 +[1,0]:INFO:root:Epoch[20] Rank[0] Batch[1251] Time cost=398.88 Train-metric=0.021911 +[1,0]:INFO:root:Epoch[20] Speed: 3211.57 samples/sec +[1,0]:INFO:root:Epoch[21] Batch[100] Loss[2.865] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[100] rmse=0.021725 lr=0.396385 +[1,0]:INFO:root:Epoch[21] Batch[200] Loss[4.129] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[200] rmse=0.021709 lr=0.396349 +[1,0]:INFO:root:Epoch[21] Batch[300] Loss[3.403] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[300] rmse=0.021724 lr=0.396313 +[1,0]:INFO:root:Epoch[21] Batch[400] Loss[3.354] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[400] rmse=0.021786 lr=0.396276 +[1,0]:INFO:root:Epoch[21] Batch[500] Loss[4.422] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[500] rmse=0.021802 lr=0.396240 +[1,0]:INFO:root:Epoch[21] Batch[600] Loss[4.552] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[600] rmse=0.021832 lr=0.396203 +[1,0]:INFO:root:Epoch[21] Batch[700] Loss[5.124] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[700] rmse=0.021880 lr=0.396166 +[1,0]:INFO:root:Epoch[21] Batch[800] Loss[3.032] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[800] rmse=0.021924 lr=0.396129 +[1,0]:INFO:root:Epoch[21] Batch[900] Loss[4.796] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[900] rmse=0.021964 lr=0.396092 +[1,0]:INFO:root:Epoch[21] Batch[1000] Loss[3.081] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[1000] rmse=0.021949 lr=0.396055 +[1,0]:INFO:root:Epoch[21] Batch[1100] Loss[4.386] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[1100] rmse=0.021940 lr=0.396017 +[1,0]:INFO:root:Epoch[21] Batch[1200] Loss[3.084] +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[1200] rmse=0.021947 lr=0.395980 +[1,0]:INFO:root:Epoch[21] Rank[0] Batch[1251] Time cost=399.05 Train-metric=0.021936 +[1,0]:INFO:root:Epoch[21] Speed: 3210.16 samples/sec +[1,0]:INFO:root:Epoch[22] Batch[100] Loss[4.694] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[100] rmse=0.021702 lr=0.395922 +[1,0]:INFO:root:Epoch[22] Batch[200] Loss[3.172] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[200] rmse=0.021783 lr=0.395884 +[1,0]:INFO:root:Epoch[22] Batch[300] Loss[5.290] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[300] rmse=0.021784 lr=0.395846 +[1,0]:INFO:root:Epoch[22] Batch[400] Loss[5.300] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[400] rmse=0.021820 lr=0.395807 +[1,0]:INFO:root:Epoch[22] Batch[500] Loss[5.284] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[500] rmse=0.021811 lr=0.395769 +[1,0]:INFO:root:Epoch[22] Batch[600] Loss[2.996] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[600] rmse=0.021833 lr=0.395730 +[1,0]:INFO:root:Epoch[22] Batch[700] Loss[5.554] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[700] rmse=0.021843 lr=0.395691 +[1,0]:INFO:root:Epoch[22] Batch[800] Loss[3.022] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[800] rmse=0.021845 lr=0.395652 +[1,0]:INFO:root:Epoch[22] Batch[900] Loss[5.453] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[900] rmse=0.021843 lr=0.395612 +[1,0]:INFO:root:Epoch[22] Batch[1000] Loss[2.950] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[1000] rmse=0.021851 lr=0.395573 +[1,0]:INFO:root:Epoch[22] Batch[1100] Loss[3.818] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[1100] rmse=0.021845 lr=0.395533 +[1,0]:INFO:root:Epoch[22] Batch[1200] Loss[3.454] +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[1200] rmse=0.021867 lr=0.395493 +[1,0]:INFO:root:Epoch[22] Rank[0] Batch[1251] Time cost=398.56 Train-metric=0.021867 +[1,0]:INFO:root:Epoch[22] Speed: 3214.13 samples/sec +[1,0]:INFO:root:Epoch[23] Batch[100] Loss[2.999] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[100] rmse=0.022039 lr=0.395433 +[1,0]:INFO:root:Epoch[23] Batch[200] Loss[5.396] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[200] rmse=0.021939 lr=0.395392 +[1,0]:INFO:root:Epoch[23] Batch[300] Loss[3.292] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[300] rmse=0.021934 lr=0.395352 +[1,0]:INFO:root:Epoch[23] Batch[400] Loss[3.039] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[400] rmse=0.021894 lr=0.395311 +[1,0]:INFO:root:Epoch[23] Batch[500] Loss[3.190] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[500] rmse=0.021860 lr=0.395270 +[1,0]:INFO:root:Epoch[23] Batch[600] Loss[3.744] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[600] rmse=0.021849 lr=0.395229 +[1,0]:INFO:root:Epoch[23] Batch[700] Loss[3.085] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[700] rmse=0.021849 lr=0.395188 +[1,0]:INFO:root:Epoch[23] Batch[800] Loss[5.211] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[800] rmse=0.021861 lr=0.395147 +[1,0]:INFO:root:Epoch[23] Batch[900] Loss[3.249] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[900] rmse=0.021846 lr=0.395105 +[1,0]:INFO:root:Epoch[23] Batch[1000] Loss[3.691] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[1000] rmse=0.021847 lr=0.395063 +[1,0]:INFO:root:Epoch[23] Batch[1100] Loss[3.050] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[1100] rmse=0.021846 lr=0.395022 +[1,0]:INFO:root:Epoch[23] Batch[1200] Loss[3.155] +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[1200] rmse=0.021863 lr=0.394980 +[1,0]:INFO:root:Epoch[23] Rank[0] Batch[1251] Time cost=399.75 Train-metric=0.021868 +[1,0]:INFO:root:Epoch[23] Speed: 3204.53 samples/sec +[1,0]:INFO:root:Epoch[24] Batch[100] Loss[5.036] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[100] rmse=0.021684 lr=0.394916 +[1,0]:INFO:root:Epoch[24] Batch[200] Loss[3.987] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[200] rmse=0.021698 lr=0.394873 +[1,0]:INFO:root:Epoch[24] Batch[300] Loss[3.061] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[300] rmse=0.021754 lr=0.394830 +[1,0]:INFO:root:Epoch[24] Batch[400] Loss[5.363] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[400] rmse=0.021748 lr=0.394788 +[1,0]:INFO:root:Epoch[24] Batch[500] Loss[3.378] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[500] rmse=0.021795 lr=0.394745 +[1,0]:INFO:root:Epoch[24] Batch[600] Loss[3.448] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[600] rmse=0.021809 lr=0.394701 +[1,0]:INFO:root:Epoch[24] Batch[700] Loss[3.718] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[700] rmse=0.021783 lr=0.394658 +[1,0]:INFO:root:Epoch[24] Batch[800] Loss[3.143] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[800] rmse=0.021799 lr=0.394614 +[1,0]:INFO:root:Epoch[24] Batch[900] Loss[3.238] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[900] rmse=0.021799 lr=0.394571 +[1,0]:INFO:root:Epoch[24] Batch[1000] Loss[3.088] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[1000] rmse=0.021813 lr=0.394527 +[1,0]:INFO:root:Epoch[24] Batch[1100] Loss[4.933] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[1100] rmse=0.021819 lr=0.394483 +[1,0]:INFO:root:Epoch[24] Batch[1200] Loss[3.643] +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[1200] rmse=0.021828 lr=0.394438 +[1,0]:INFO:root:Epoch[24] Rank[0] Batch[1251] Time cost=397.96 Train-metric=0.021828 +[1,0]:INFO:root:Epoch[24] Speed: 3218.94 samples/sec +[1,0]:INFO:root:Epoch[24] Rank[0] Validation-accuracy=0.531960 Validation-top_k_accuracy_5=0.786180 +[1,0]:INFO:root:Epoch[25] Batch[100] Loss[3.232] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[100] rmse=0.021801 lr=0.394371 +[1,0]:INFO:root:Epoch[25] Batch[200] Loss[3.391] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[200] rmse=0.021717 lr=0.394326 +[1,0]:INFO:root:Epoch[25] Batch[300] Loss[5.224] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[300] rmse=0.021775 lr=0.394282 +[1,0]:INFO:root:Epoch[25] Batch[400] Loss[3.211] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[400] rmse=0.021759 lr=0.394237 +[1,0]:INFO:root:Epoch[25] Batch[500] Loss[3.630] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[500] rmse=0.021729 lr=0.394191 +[1,0]:INFO:root:Epoch[25] Batch[600] Loss[4.279] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[600] rmse=0.021727 lr=0.394146 +[1,0]:INFO:root:Epoch[25] Batch[700] Loss[3.589] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[700] rmse=0.021715 lr=0.394100 +[1,0]:INFO:root:Epoch[25] Batch[800] Loss[4.696] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[800] rmse=0.021719 lr=0.394055 +[1,0]:INFO:root:Epoch[25] Batch[900] Loss[3.439] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[900] rmse=0.021745 lr=0.394009 +[1,0]:INFO:root:Epoch[25] Batch[1000] Loss[3.385] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[1000] rmse=0.021767 lr=0.393963 +[1,0]:INFO:root:Epoch[25] Batch[1100] Loss[3.410] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[1100] rmse=0.021769 lr=0.393916 +[1,0]:INFO:root:Epoch[25] Batch[1200] Loss[3.544] +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[1200] rmse=0.021775 lr=0.393870 +[1,0]:INFO:root:Epoch[25] Rank[0] Batch[1251] Time cost=400.61 Train-metric=0.021783 +[1,0]:INFO:root:Epoch[25] Speed: 3197.65 samples/sec +[1,0]:INFO:root:Epoch[26] Batch[100] Loss[4.576] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[100] rmse=0.021780 lr=0.393799 +[1,0]:INFO:root:Epoch[26] Batch[200] Loss[4.336] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[200] rmse=0.021708 lr=0.393753 +[1,0]:INFO:root:Epoch[26] Batch[300] Loss[3.887] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[300] rmse=0.021696 lr=0.393706 +[1,0]:INFO:root:Epoch[26] Batch[400] Loss[3.050] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[400] rmse=0.021691 lr=0.393658 +[1,0]:INFO:root:Epoch[26] Batch[500] Loss[3.177] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[500] rmse=0.021727 lr=0.393611 +[1,0]:INFO:root:Epoch[26] Batch[600] Loss[3.246] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[600] rmse=0.021715 lr=0.393563 +[1,0]:INFO:root:Epoch[26] Batch[700] Loss[3.092] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[700] rmse=0.021703 lr=0.393516 +[1,0]:INFO:root:Epoch[26] Batch[800] Loss[4.335] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[800] rmse=0.021717 lr=0.393468 +[1,0]:INFO:root:Epoch[26] Batch[900] Loss[3.080] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[900] rmse=0.021710 lr=0.393420 +[1,0]:INFO:root:Epoch[26] Batch[1000] Loss[4.177] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[1000] rmse=0.021726 lr=0.393371 +[1,0]:INFO:root:Epoch[26] Batch[1100] Loss[3.319] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[1100] rmse=0.021732 lr=0.393323 +[1,0]:INFO:root:Epoch[26] Batch[1200] Loss[5.379] +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[1200] rmse=0.021722 lr=0.393274 +[1,0]:INFO:root:Epoch[26] Rank[0] Batch[1251] Time cost=401.40 Train-metric=0.021729 +[1,0]:INFO:root:Epoch[26] Speed: 3191.40 samples/sec +[1,0]:INFO:root:Epoch[27] Batch[100] Loss[3.422] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[100] rmse=0.021691 lr=0.393201 +[1,0]:INFO:root:Epoch[27] Batch[200] Loss[3.013] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[200] rmse=0.021716 lr=0.393151 +[1,0]:INFO:root:Epoch[27] Batch[300] Loss[4.942] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[300] rmse=0.021790 lr=0.393102 +[1,0]:INFO:root:Epoch[27] Batch[400] Loss[2.949] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[400] rmse=0.021801 lr=0.393053 +[1,0]:INFO:root:Epoch[27] Batch[500] Loss[5.223] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[500] rmse=0.021791 lr=0.393003 +[1,0]:INFO:root:Epoch[27] Batch[600] Loss[3.337] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[600] rmse=0.021785 lr=0.392954 +[1,0]:INFO:root:Epoch[27] Batch[700] Loss[4.276] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[700] rmse=0.021793 lr=0.392904 +[1,0]:INFO:root:Epoch[27] Batch[800] Loss[3.160] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[800] rmse=0.021771 lr=0.392854 +[1,0]:INFO:root:Epoch[27] Batch[900] Loss[3.163] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[900] rmse=0.021785 lr=0.392803 +[1,0]:INFO:root:Epoch[27] Batch[1000] Loss[4.486] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[1000] rmse=0.021788 lr=0.392753 +[1,0]:INFO:root:Epoch[27] Batch[1100] Loss[3.190] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[1100] rmse=0.021798 lr=0.392702 +[1,0]:INFO:root:Epoch[27] Batch[1200] Loss[3.578] +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[1200] rmse=0.021798 lr=0.392651 +[1,0]:INFO:root:Epoch[27] Rank[0] Batch[1251] Time cost=401.40 Train-metric=0.021795 +[1,0]:INFO:root:Epoch[27] Speed: 3191.42 samples/sec +[1,0]:INFO:root:Epoch[28] Batch[100] Loss[5.269] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[100] rmse=0.021677 lr=0.392574 +[1,0]:INFO:root:Epoch[28] Batch[200] Loss[2.825] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[200] rmse=0.021690 lr=0.392523 +[1,0]:INFO:root:Epoch[28] Batch[300] Loss[3.059] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[300] rmse=0.021718 lr=0.392472 +[1,0]:INFO:root:Epoch[28] Batch[400] Loss[2.957] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[400] rmse=0.021699 lr=0.392420 +[1,0]:INFO:root:Epoch[28] Batch[500] Loss[5.123] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[500] rmse=0.021707 lr=0.392369 +[1,0]:INFO:root:Epoch[28] Batch[600] Loss[3.092] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[600] rmse=0.021719 lr=0.392317 +[1,0]:INFO:root:Epoch[28] Batch[700] Loss[2.837] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[700] rmse=0.021707 lr=0.392265 +[1,0]:INFO:root:Epoch[28] Batch[800] Loss[3.152] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[800] rmse=0.021726 lr=0.392212 +[1,0]:INFO:root:Epoch[28] Batch[900] Loss[4.948] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[900] rmse=0.021745 lr=0.392160 +[1,0]:INFO:root:Epoch[28] Batch[1000] Loss[3.132] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[1000] rmse=0.021750 lr=0.392107 +[1,0]:INFO:root:Epoch[28] Batch[1100] Loss[3.140] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[1100] rmse=0.021757 lr=0.392055 +[1,0]:INFO:root:Epoch[28] Batch[1200] Loss[4.988] +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[1200] rmse=0.021743 lr=0.392002 +[1,0]:INFO:root:Epoch[28] Rank[0] Batch[1251] Time cost=399.29 Train-metric=0.021753 +[1,0]:INFO:root:Epoch[28] Speed: 3208.22 samples/sec +[1,0]:INFO:root:Epoch[29] Batch[100] Loss[3.385] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[100] rmse=0.021609 lr=0.391921 +[1,0]:INFO:root:Epoch[29] Batch[200] Loss[3.850] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[200] rmse=0.021547 lr=0.391868 +[1,0]:INFO:root:Epoch[29] Batch[300] Loss[3.472] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[300] rmse=0.021542 lr=0.391815 +[1,0]:INFO:root:Epoch[29] Batch[400] Loss[4.938] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[400] rmse=0.021587 lr=0.391761 +[1,0]:INFO:root:Epoch[29] Batch[500] Loss[2.865] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[500] rmse=0.021614 lr=0.391707 +[1,0]:INFO:root:Epoch[29] Batch[600] Loss[3.397] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[600] rmse=0.021649 lr=0.391653 +[1,0]:INFO:root:Epoch[29] Batch[700] Loss[2.957] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[700] rmse=0.021642 lr=0.391599 +[1,0]:INFO:root:Epoch[29] Batch[800] Loss[5.390] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[800] rmse=0.021642 lr=0.391544 +[1,0]:INFO:root:Epoch[29] Batch[900] Loss[3.185] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[900] rmse=0.021666 lr=0.391490 +[1,0]:INFO:root:Epoch[29] Batch[1000] Loss[4.188] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[1000] rmse=0.021668 lr=0.391435 +[1,0]:INFO:root:Epoch[29] Batch[1100] Loss[3.405] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[1100] rmse=0.021664 lr=0.391380 +[1,0]:INFO:root:Epoch[29] Batch[1200] Loss[5.060] +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[1200] rmse=0.021672 lr=0.391325 +[1,0]:INFO:root:Epoch[29] Rank[0] Batch[1251] Time cost=399.33 Train-metric=0.021676 +[1,0]:INFO:root:Epoch[29] Speed: 3207.90 samples/sec +[1,0]:INFO:root:Epoch[29] Rank[0] Validation-accuracy=0.528540 Validation-top_k_accuracy_5=0.779280 +[1,0]:INFO:root:Epoch[30] Batch[100] Loss[3.367] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[100] rmse=0.021622 lr=0.391241 +[1,0]:INFO:root:Epoch[30] Batch[200] Loss[3.122] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[200] rmse=0.021615 lr=0.391186 +[1,0]:INFO:root:Epoch[30] Batch[300] Loss[3.229] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[300] rmse=0.021658 lr=0.391130 +[1,0]:INFO:root:Epoch[30] Batch[400] Loss[3.281] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[400] rmse=0.021680 lr=0.391074 +[1,0]:INFO:root:Epoch[30] Batch[500] Loss[2.971] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[500] rmse=0.021671 lr=0.391018 +[1,0]:INFO:root:Epoch[30] Batch[600] Loss[3.153] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[600] rmse=0.021644 lr=0.390962 +[1,0]:INFO:root:Epoch[30] Batch[700] Loss[3.551] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[700] rmse=0.021703 lr=0.390906 +[1,0]:INFO:root:Epoch[30] Batch[800] Loss[5.289] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[800] rmse=0.021697 lr=0.390849 +[1,0]:INFO:root:Epoch[30] Batch[900] Loss[2.833] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[900] rmse=0.021680 lr=0.390793 +[1,0]:INFO:root:Epoch[30] Batch[1000] Loss[4.397] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[1000] rmse=0.021655 lr=0.390736 +[1,0]:INFO:root:Epoch[30] Batch[1100] Loss[2.828] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[1100] rmse=0.021675 lr=0.390679 +[1,0]:INFO:root:Epoch[30] Batch[1200] Loss[3.132] +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[1200] rmse=0.021669 lr=0.390621 +[1,0]:INFO:root:Epoch[30] Rank[0] Batch[1251] Time cost=399.77 Train-metric=0.021684 +[1,0]:INFO:root:Epoch[30] Speed: 3204.37 samples/sec +[1,0]:INFO:root:Epoch[31] Batch[100] Loss[5.485] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[100] rmse=0.021377 lr=0.390535 +[1,0]:INFO:root:Epoch[31] Batch[200] Loss[3.068] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[200] rmse=0.021335 lr=0.390477 +[1,0]:INFO:root:Epoch[31] Batch[300] Loss[3.336] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[300] rmse=0.021432 lr=0.390419 +[1,0]:INFO:root:Epoch[31] Batch[400] Loss[4.108] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[400] rmse=0.021479 lr=0.390361 +[1,0]:INFO:root:Epoch[31] Batch[500] Loss[5.506] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[500] rmse=0.021523 lr=0.390303 +[1,0]:INFO:root:Epoch[31] Batch[600] Loss[3.279] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[600] rmse=0.021554 lr=0.390245 +[1,0]:INFO:root:Epoch[31] Batch[700] Loss[3.336] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[700] rmse=0.021600 lr=0.390186 +[1,0]:INFO:root:Epoch[31] Batch[800] Loss[3.369] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[800] rmse=0.021625 lr=0.390127 +[1,0]:INFO:root:Epoch[31] Batch[900] Loss[5.516] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[900] rmse=0.021647 lr=0.390069 +[1,0]:INFO:root:Epoch[31] Batch[1000] Loss[2.971] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[1000] rmse=0.021668 lr=0.390010 +[1,0]:INFO:root:Epoch[31] Batch[1100] Loss[5.113] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[1100] rmse=0.021671 lr=0.389950 +[1,0]:INFO:root:Epoch[31] Batch[1200] Loss[3.086] +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[1200] rmse=0.021680 lr=0.389891 +[1,0]:INFO:root:Epoch[31] Rank[0] Batch[1251] Time cost=398.77 Train-metric=0.021670 +[1,0]:INFO:root:Epoch[31] Speed: 3212.43 samples/sec +[1,0]:INFO:root:Epoch[32] Batch[100] Loss[2.988] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[100] rmse=0.021437 lr=0.389801 +[1,0]:INFO:root:Epoch[32] Batch[200] Loss[5.326] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[200] rmse=0.021553 lr=0.389741 +[1,0]:INFO:root:Epoch[32] Batch[300] Loss[3.390] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[300] rmse=0.021707 lr=0.389681 +[1,0]:INFO:root:Epoch[32] Batch[400] Loss[3.074] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[400] rmse=0.021672 lr=0.389621 +[1,0]:INFO:root:Epoch[32] Batch[500] Loss[3.141] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[500] rmse=0.021618 lr=0.389561 +[1,0]:INFO:root:Epoch[32] Batch[600] Loss[4.619] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[600] rmse=0.021597 lr=0.389500 +[1,0]:INFO:root:Epoch[32] Batch[700] Loss[4.071] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[700] rmse=0.021616 lr=0.389440 +[1,0]:INFO:root:Epoch[32] Batch[800] Loss[3.171] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[800] rmse=0.021625 lr=0.389379 +[1,0]:INFO:root:Epoch[32] Batch[900] Loss[3.087] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[900] rmse=0.021655 lr=0.389318 +[1,0]:INFO:root:Epoch[32] Batch[1000] Loss[3.725] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[1000] rmse=0.021665 lr=0.389257 +[1,0]:INFO:root:Epoch[32] Batch[1100] Loss[3.324] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[1100] rmse=0.021667 lr=0.389196 +[1,0]:INFO:root:Epoch[32] Batch[1200] Loss[3.290] +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[1200] rmse=0.021673 lr=0.389134 +[1,0]:INFO:root:Epoch[32] Rank[0] Batch[1251] Time cost=399.25 Train-metric=0.021692 +[1,0]:INFO:root:Epoch[32] Speed: 3208.57 samples/sec +[1,0]:INFO:root:Epoch[33] Batch[100] Loss[3.613] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[100] rmse=0.021639 lr=0.389041 +[1,0]:INFO:root:Epoch[33] Batch[200] Loss[3.054] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[200] rmse=0.021776 lr=0.388979 +[1,0]:INFO:root:Epoch[33] Batch[300] Loss[2.739] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[300] rmse=0.021620 lr=0.388917 +[1,0]:INFO:root:Epoch[33] Batch[400] Loss[3.896] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[400] rmse=0.021627 lr=0.388855 +[1,0]:INFO:root:Epoch[33] Batch[500] Loss[3.448] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[500] rmse=0.021665 lr=0.388792 +[1,0]:INFO:root:Epoch[33] Batch[600] Loss[2.614] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[600] rmse=0.021650 lr=0.388730 +[1,0]:INFO:root:Epoch[33] Batch[700] Loss[3.200] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[700] rmse=0.021649 lr=0.388667 +[1,0]:INFO:root:Epoch[33] Batch[800] Loss[4.616] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[800] rmse=0.021658 lr=0.388604 +[1,0]:INFO:root:Epoch[33] Batch[900] Loss[3.096] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[900] rmse=0.021667 lr=0.388541 +[1,0]:INFO:root:Epoch[33] Batch[1000] Loss[3.212] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[1000] rmse=0.021645 lr=0.388478 +[1,0]:INFO:root:Epoch[33] Batch[1100] Loss[4.747] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[1100] rmse=0.021634 lr=0.388414 +[1,0]:INFO:root:Epoch[33] Batch[1200] Loss[5.062] +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[1200] rmse=0.021640 lr=0.388351 +[1,0]:INFO:root:Epoch[33] Rank[0] Batch[1251] Time cost=400.03 Train-metric=0.021633 +[1,0]:INFO:root:Epoch[33] Speed: 3202.30 samples/sec +[1,0]:INFO:root:Epoch[34] Batch[100] Loss[3.578] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[100] rmse=0.021445 lr=0.388254 +[1,0]:INFO:root:Epoch[34] Batch[200] Loss[3.028] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[200] rmse=0.021628 lr=0.388190 +[1,0]:INFO:root:Epoch[34] Batch[300] Loss[5.139] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[300] rmse=0.021581 lr=0.388126 +[1,0]:INFO:root:Epoch[34] Batch[400] Loss[3.252] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[400] rmse=0.021562 lr=0.388062 +[1,0]:INFO:root:Epoch[34] Batch[500] Loss[2.988] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[500] rmse=0.021583 lr=0.387997 +[1,0]:INFO:root:Epoch[34] Batch[600] Loss[3.402] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[600] rmse=0.021617 lr=0.387932 +[1,0]:INFO:root:Epoch[34] Batch[700] Loss[3.462] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[700] rmse=0.021659 lr=0.387867 +[1,0]:INFO:root:Epoch[34] Batch[800] Loss[4.733] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[800] rmse=0.021652 lr=0.387802 +[1,0]:INFO:root:Epoch[34] Batch[900] Loss[2.974] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[900] rmse=0.021657 lr=0.387737 +[1,0]:INFO:root:Epoch[34] Batch[1000] Loss[3.122] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[1000] rmse=0.021657 lr=0.387672 +[1,0]:INFO:root:Epoch[34] Batch[1100] Loss[2.892] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[1100] rmse=0.021660 lr=0.387606 +[1,0]:INFO:root:Epoch[34] Batch[1200] Loss[3.926] +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[1200] rmse=0.021658 lr=0.387541 +[1,0]:INFO:root:Epoch[34] Rank[0] Batch[1251] Time cost=398.93 Train-metric=0.021650 +[1,0]:INFO:root:Epoch[34] Speed: 3211.12 samples/sec +[1,0]:INFO:root:Epoch[34] Rank[0] Validation-accuracy=0.527620 Validation-top_k_accuracy_5=0.777500 +[1,0]:INFO:root:Epoch[35] Batch[100] Loss[3.109] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[100] rmse=0.021580 lr=0.387441 +[1,0]:INFO:root:Epoch[35] Batch[200] Loss[3.179] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[200] rmse=0.021598 lr=0.387375 +[1,0]:INFO:root:Epoch[35] Batch[300] Loss[4.290] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[300] rmse=0.021584 lr=0.387309 +[1,0]:INFO:root:Epoch[35] Batch[400] Loss[5.357] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[400] rmse=0.021572 lr=0.387242 +[1,0]:INFO:root:Epoch[35] Batch[500] Loss[4.644] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[500] rmse=0.021592 lr=0.387175 +[1,0]:INFO:root:Epoch[35] Batch[600] Loss[4.162] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[600] rmse=0.021612 lr=0.387109 +[1,0]:INFO:root:Epoch[35] Batch[700] Loss[3.281] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[700] rmse=0.021628 lr=0.387042 +[1,0]:INFO:root:Epoch[35] Batch[800] Loss[2.848] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[800] rmse=0.021617 lr=0.386975 +[1,0]:INFO:root:Epoch[35] Batch[900] Loss[3.067] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[900] rmse=0.021625 lr=0.386907 +[1,0]:INFO:root:Epoch[35] Batch[1000] Loss[5.481] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[1000] rmse=0.021626 lr=0.386840 +[1,0]:INFO:root:Epoch[35] Batch[1100] Loss[5.499] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[1100] rmse=0.021634 lr=0.386772 +[1,0]:INFO:root:Epoch[35] Batch[1200] Loss[2.835] +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[1200] rmse=0.021643 lr=0.386704 +[1,0]:INFO:root:Epoch[35] Rank[0] Batch[1251] Time cost=398.47 Train-metric=0.021646 +[1,0]:INFO:root:Epoch[35] Speed: 3214.83 samples/sec +[1,0]:INFO:root:Epoch[36] Batch[100] Loss[3.050] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[100] rmse=0.021742 lr=0.386602 +[1,0]:INFO:root:Epoch[36] Batch[200] Loss[3.186] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[200] rmse=0.021698 lr=0.386533 +[1,0]:INFO:root:Epoch[36] Batch[300] Loss[3.596] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[300] rmse=0.021570 lr=0.386465 +[1,0]:INFO:root:Epoch[36] Batch[400] Loss[3.081] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[400] rmse=0.021617 lr=0.386396 +[1,0]:INFO:root:Epoch[36] Batch[500] Loss[3.158] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[500] rmse=0.021630 lr=0.386328 +[1,0]:INFO:root:Epoch[36] Batch[600] Loss[3.006] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[600] rmse=0.021616 lr=0.386259 +[1,0]:INFO:root:Epoch[36] Batch[700] Loss[2.765] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[700] rmse=0.021599 lr=0.386190 +[1,0]:INFO:root:Epoch[36] Batch[800] Loss[3.239] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[800] rmse=0.021606 lr=0.386120 +[1,0]:INFO:root:Epoch[36] Batch[900] Loss[4.161] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[900] rmse=0.021610 lr=0.386051 +[1,0]:INFO:root:Epoch[36] Batch[1000] Loss[3.293] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[1000] rmse=0.021631 lr=0.385981 +[1,0]:INFO:root:Epoch[36] Batch[1100] Loss[5.489] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[1100] rmse=0.021611 lr=0.385912 +[1,0]:INFO:root:Epoch[36] Batch[1200] Loss[3.092] +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[1200] rmse=0.021618 lr=0.385842 +[1,0]:INFO:root:Epoch[36] Rank[0] Batch[1251] Time cost=398.76 Train-metric=0.021616 +[1,0]:INFO:root:Epoch[36] Speed: 3212.56 samples/sec +[1,0]:INFO:root:Epoch[37] Batch[100] Loss[4.797] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[100] rmse=0.021470 lr=0.385736 +[1,0]:INFO:root:Epoch[37] Batch[200] Loss[3.284] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[200] rmse=0.021568 lr=0.385666 +[1,0]:INFO:root:Epoch[37] Batch[300] Loss[3.616] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[300] rmse=0.021561 lr=0.385595 +[1,0]:INFO:root:Epoch[37] Batch[400] Loss[3.180] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[400] rmse=0.021581 lr=0.385525 +[1,0]:INFO:root:Epoch[37] Batch[500] Loss[2.869] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[500] rmse=0.021610 lr=0.385454 +[1,0]:INFO:root:Epoch[37] Batch[600] Loss[5.556] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[600] rmse=0.021579 lr=0.385383 +[1,0]:INFO:root:Epoch[37] Batch[700] Loss[4.711] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[700] rmse=0.021568 lr=0.385312 +[1,0]:INFO:root:Epoch[37] Batch[800] Loss[3.531] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[800] rmse=0.021571 lr=0.385240 +[1,0]:INFO:root:Epoch[37] Batch[900] Loss[4.009] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[900] rmse=0.021541 lr=0.385169 +[1,0]:INFO:root:Epoch[37] Batch[1000] Loss[4.705] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[1000] rmse=0.021554 lr=0.385097 +[1,0]:INFO:root:Epoch[37] Batch[1100] Loss[3.148] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[1100] rmse=0.021562 lr=0.385025 +[1,0]:INFO:root:Epoch[37] Batch[1200] Loss[3.411] +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[1200] rmse=0.021562 lr=0.384953 +[1,0]:INFO:root:Epoch[37] Rank[0] Batch[1251] Time cost=398.62 Train-metric=0.021567 +[1,0]:INFO:root:Epoch[37] Speed: 3213.61 samples/sec +[1,0]:INFO:root:Epoch[38] Batch[100] Loss[3.171] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[100] rmse=0.021414 lr=0.384844 +[1,0]:INFO:root:Epoch[38] Batch[200] Loss[2.977] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[200] rmse=0.021451 lr=0.384772 +[1,0]:INFO:root:Epoch[38] Batch[300] Loss[3.006] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[300] rmse=0.021467 lr=0.384699 +[1,0]:INFO:root:Epoch[38] Batch[400] Loss[5.053] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[400] rmse=0.021507 lr=0.384627 +[1,0]:INFO:root:Epoch[38] Batch[500] Loss[3.713] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[500] rmse=0.021541 lr=0.384554 +[1,0]:INFO:root:Epoch[38] Batch[600] Loss[3.996] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[600] rmse=0.021569 lr=0.384481 +[1,0]:INFO:root:Epoch[38] Batch[700] Loss[4.842] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[700] rmse=0.021568 lr=0.384407 +[1,0]:INFO:root:Epoch[38] Batch[800] Loss[2.947] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[800] rmse=0.021574 lr=0.384334 +[1,0]:INFO:root:Epoch[38] Batch[900] Loss[3.508] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[900] rmse=0.021572 lr=0.384260 +[1,0]:INFO:root:Epoch[38] Batch[1000] Loss[3.033] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[1000] rmse=0.021563 lr=0.384187 +[1,0]:INFO:root:Epoch[38] Batch[1100] Loss[2.931] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[1100] rmse=0.021568 lr=0.384113 +[1,0]:INFO:root:Epoch[38] Batch[1200] Loss[3.100] +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[1200] rmse=0.021598 lr=0.384039 +[1,0]:INFO:root:Epoch[38] Rank[0] Batch[1251] Time cost=399.39 Train-metric=0.021599 +[1,0]:INFO:root:Epoch[38] Speed: 3207.46 samples/sec +[1,0]:INFO:root:Epoch[39] Batch[100] Loss[3.038] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[100] rmse=0.021666 lr=0.383927 +[1,0]:INFO:root:Epoch[39] Batch[200] Loss[5.365] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[200] rmse=0.021607 lr=0.383852 +[1,0]:INFO:root:Epoch[39] Batch[300] Loss[5.126] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[300] rmse=0.021585 lr=0.383778 +[1,0]:INFO:root:Epoch[39] Batch[400] Loss[4.682] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[400] rmse=0.021574 lr=0.383703 +[1,0]:INFO:root:Epoch[39] Batch[500] Loss[2.973] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[500] rmse=0.021565 lr=0.383628 +[1,0]:INFO:root:Epoch[39] Batch[600] Loss[2.814] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[600] rmse=0.021541 lr=0.383553 +[1,0]:INFO:root:Epoch[39] Batch[700] Loss[4.271] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[700] rmse=0.021570 lr=0.383477 +[1,0]:INFO:root:Epoch[39] Batch[800] Loss[3.317] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[800] rmse=0.021594 lr=0.383402 +[1,0]:INFO:root:Epoch[39] Batch[900] Loss[3.161] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[900] rmse=0.021617 lr=0.383326 +[1,0]:INFO:root:Epoch[39] Batch[1000] Loss[3.235] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[1000] rmse=0.021613 lr=0.383251 +[1,0]:INFO:root:Epoch[39] Batch[1100] Loss[2.713] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[1100] rmse=0.021617 lr=0.383175 +[1,0]:INFO:root:Epoch[39] Batch[1200] Loss[4.568] +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[1200] rmse=0.021607 lr=0.383099 +[1,0]:INFO:root:Epoch[39] Rank[0] Batch[1251] Time cost=398.50 Train-metric=0.021606 +[1,0]:INFO:root:Epoch[39] Speed: 3214.60 samples/sec +[1,0]:INFO:root:Epoch[39] Rank[0] Validation-accuracy=0.546820 Validation-top_k_accuracy_5=0.792020 +[1,0]:INFO:root:Epoch[40] Batch[100] Loss[3.030] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[100] rmse=0.021646 lr=0.382983 +[1,0]:INFO:root:Epoch[40] Batch[200] Loss[3.205] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[200] rmse=0.021604 lr=0.382907 +[1,0]:INFO:root:Epoch[40] Batch[300] Loss[4.347] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[300] rmse=0.021652 lr=0.382830 +[1,0]:INFO:root:Epoch[40] Batch[400] Loss[3.302] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[400] rmse=0.021608 lr=0.382753 +[1,0]:INFO:root:Epoch[40] Batch[500] Loss[5.204] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[500] rmse=0.021590 lr=0.382676 +[1,0]:INFO:root:Epoch[40] Batch[600] Loss[3.464] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[600] rmse=0.021593 lr=0.382599 +[1,0]:INFO:root:Epoch[40] Batch[700] Loss[2.883] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[700] rmse=0.021577 lr=0.382522 +[1,0]:INFO:root:Epoch[40] Batch[800] Loss[3.143] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[800] rmse=0.021576 lr=0.382444 +[1,0]:INFO:root:Epoch[40] Batch[900] Loss[3.218] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[900] rmse=0.021579 lr=0.382367 +[1,0]:INFO:root:Epoch[40] Batch[1000] Loss[3.611] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[1000] rmse=0.021614 lr=0.382289 +[1,0]:INFO:root:Epoch[40] Batch[1100] Loss[3.869] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[1100] rmse=0.021619 lr=0.382211 +[1,0]:INFO:root:Epoch[40] Batch[1200] Loss[2.914] +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[1200] rmse=0.021609 lr=0.382133 +[1,0]:INFO:root:Epoch[40] Rank[0] Batch[1251] Time cost=396.76 Train-metric=0.021618 +[1,0]:INFO:root:Epoch[40] Speed: 3228.72 samples/sec +[1,0]:INFO:root:Epoch[41] Batch[100] Loss[2.943] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[100] rmse=0.021391 lr=0.382014 +[1,0]:INFO:root:Epoch[41] Batch[200] Loss[5.351] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[200] rmse=0.021457 lr=0.381936 +[1,0]:INFO:root:Epoch[41] Batch[300] Loss[2.813] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[300] rmse=0.021496 lr=0.381857 +[1,0]:INFO:root:Epoch[41] Batch[400] Loss[2.963] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[400] rmse=0.021478 lr=0.381778 +[1,0]:INFO:root:Epoch[41] Batch[500] Loss[2.965] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[500] rmse=0.021481 lr=0.381699 +[1,0]:INFO:root:Epoch[41] Batch[600] Loss[2.932] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[600] rmse=0.021453 lr=0.381620 +[1,0]:INFO:root:Epoch[41] Batch[700] Loss[5.574] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[700] rmse=0.021466 lr=0.381540 +[1,0]:INFO:root:Epoch[41] Batch[800] Loss[4.149] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[800] rmse=0.021488 lr=0.381461 +[1,0]:INFO:root:Epoch[41] Batch[900] Loss[5.206] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[900] rmse=0.021520 lr=0.381381 +[1,0]:INFO:root:Epoch[41] Batch[1000] Loss[5.245] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[1000] rmse=0.021528 lr=0.381301 +[1,0]:INFO:root:Epoch[41] Batch[1100] Loss[3.717] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[1100] rmse=0.021550 lr=0.381221 +[1,0]:INFO:root:Epoch[41] Batch[1200] Loss[4.106] +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[1200] rmse=0.021551 lr=0.381141 +[1,0]:INFO:root:Epoch[41] Rank[0] Batch[1251] Time cost=398.49 Train-metric=0.021566 +[1,0]:INFO:root:Epoch[41] Speed: 3214.71 samples/sec +[1,0]:INFO:root:Epoch[42] Batch[100] Loss[3.573] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[100] rmse=0.021386 lr=0.381020 +[1,0]:INFO:root:Epoch[42] Batch[200] Loss[3.900] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[200] rmse=0.021486 lr=0.380939 +[1,0]:INFO:root:Epoch[42] Batch[300] Loss[5.588] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[300] rmse=0.021357 lr=0.380858 +[1,0]:INFO:root:Epoch[42] Batch[400] Loss[5.327] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[400] rmse=0.021389 lr=0.380777 +[1,0]:INFO:root:Epoch[42] Batch[500] Loss[3.437] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[500] rmse=0.021454 lr=0.380696 +[1,0]:INFO:root:Epoch[42] Batch[600] Loss[2.931] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[600] rmse=0.021503 lr=0.380615 +[1,0]:INFO:root:Epoch[42] Batch[700] Loss[4.870] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[700] rmse=0.021508 lr=0.380533 +[1,0]:INFO:root:Epoch[42] Batch[800] Loss[3.482] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[800] rmse=0.021486 lr=0.380452 +[1,0]:INFO:root:Epoch[42] Batch[900] Loss[5.467] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[900] rmse=0.021488 lr=0.380370 +[1,0]:INFO:root:Epoch[42] Batch[1000] Loss[3.004] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[1000] rmse=0.021493 lr=0.380288 +[1,0]:INFO:root:Epoch[42] Batch[1100] Loss[4.107] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[1100] rmse=0.021506 lr=0.380206 +[1,0]:INFO:root:Epoch[42] Batch[1200] Loss[3.040] +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[1200] rmse=0.021516 lr=0.380124 +[1,0]:INFO:root:Epoch[42] Rank[0] Batch[1251] Time cost=398.89 Train-metric=0.021521 +[1,0]:INFO:root:Epoch[42] Speed: 3211.48 samples/sec +[1,0]:INFO:root:Epoch[43] Batch[100] Loss[2.961] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[100] rmse=0.021440 lr=0.380000 +[1,0]:INFO:root:Epoch[43] Batch[200] Loss[4.058] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[200] rmse=0.021408 lr=0.379917 +[1,0]:INFO:root:Epoch[43] Batch[300] Loss[3.181] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[300] rmse=0.021437 lr=0.379834 +[1,0]:INFO:root:Epoch[43] Batch[400] Loss[3.092] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[400] rmse=0.021387 lr=0.379751 +[1,0]:INFO:root:Epoch[43] Batch[500] Loss[5.258] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[500] rmse=0.021352 lr=0.379668 +[1,0]:INFO:root:Epoch[43] Batch[600] Loss[3.839] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[600] rmse=0.021354 lr=0.379585 +[1,0]:INFO:root:Epoch[43] Batch[700] Loss[2.943] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[700] rmse=0.021367 lr=0.379501 +[1,0]:INFO:root:Epoch[43] Batch[800] Loss[3.506] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[800] rmse=0.021400 lr=0.379418 +[1,0]:INFO:root:Epoch[43] Batch[900] Loss[3.147] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[900] rmse=0.021414 lr=0.379334 +[1,0]:INFO:root:Epoch[43] Batch[1000] Loss[4.874] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[1000] rmse=0.021430 lr=0.379250 +[1,0]:INFO:root:Epoch[43] Batch[1100] Loss[3.064] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[1100] rmse=0.021459 lr=0.379166 +[1,0]:INFO:root:Epoch[43] Batch[1200] Loss[3.948] +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[1200] rmse=0.021452 lr=0.379082 +[1,0]:INFO:root:Epoch[43] Rank[0] Batch[1251] Time cost=399.33 Train-metric=0.021457 +[1,0]:INFO:root:Epoch[43] Speed: 3207.93 samples/sec +[1,0]:INFO:root:Epoch[44] Batch[100] Loss[3.116] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[100] rmse=0.021577 lr=0.378954 +[1,0]:INFO:root:Epoch[44] Batch[200] Loss[3.157] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[200] rmse=0.021563 lr=0.378870 +[1,0]:INFO:root:Epoch[44] Batch[300] Loss[2.808] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[300] rmse=0.021562 lr=0.378785 +[1,0]:INFO:root:Epoch[44] Batch[400] Loss[3.001] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[400] rmse=0.021532 lr=0.378700 +[1,0]:INFO:root:Epoch[44] Batch[500] Loss[3.273] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[500] rmse=0.021536 lr=0.378615 +[1,0]:INFO:root:Epoch[44] Batch[600] Loss[3.010] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[600] rmse=0.021531 lr=0.378529 +[1,0]:INFO:root:Epoch[44] Batch[700] Loss[3.252] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[700] rmse=0.021532 lr=0.378444 +[1,0]:INFO:root:Epoch[44] Batch[800] Loss[3.991] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[800] rmse=0.021553 lr=0.378358 +[1,0]:INFO:root:Epoch[44] Batch[900] Loss[2.941] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[900] rmse=0.021576 lr=0.378273 +[1,0]:INFO:root:Epoch[44] Batch[1000] Loss[3.222] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[1000] rmse=0.021581 lr=0.378187 +[1,0]:INFO:root:Epoch[44] Batch[1100] Loss[5.558] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[1100] rmse=0.021566 lr=0.378101 +[1,0]:INFO:root:Epoch[44] Batch[1200] Loss[4.737] +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[1200] rmse=0.021569 lr=0.378014 +[1,0]:INFO:root:Epoch[44] Rank[0] Batch[1251] Time cost=402.95 Train-metric=0.021561 +[1,0]:INFO:root:Epoch[44] Speed: 3179.12 samples/sec +[1,0]:INFO:root:Epoch[44] Rank[0] Validation-accuracy=0.559860 Validation-top_k_accuracy_5=0.803180 +[1,0]:INFO:root:Epoch[45] Batch[100] Loss[5.134] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[100] rmse=0.021405 lr=0.377884 +[1,0]:INFO:root:Epoch[45] Batch[200] Loss[3.143] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[200] rmse=0.021526 lr=0.377797 +[1,0]:INFO:root:Epoch[45] Batch[300] Loss[3.217] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[300] rmse=0.021417 lr=0.377710 +[1,0]:INFO:root:Epoch[45] Batch[400] Loss[2.983] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[400] rmse=0.021445 lr=0.377623 +[1,0]:INFO:root:Epoch[45] Batch[500] Loss[5.234] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[500] rmse=0.021445 lr=0.377536 +[1,0]:INFO:root:Epoch[45] Batch[600] Loss[4.147] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[600] rmse=0.021464 lr=0.377449 +[1,0]:INFO:root:Epoch[45] Batch[700] Loss[3.080] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[700] rmse=0.021471 lr=0.377362 +[1,0]:INFO:root:Epoch[45] Batch[800] Loss[5.345] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[800] rmse=0.021463 lr=0.377274 +[1,0]:INFO:root:Epoch[45] Batch[900] Loss[3.278] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[900] rmse=0.021493 lr=0.377186 +[1,0]:INFO:root:Epoch[45] Batch[1000] Loss[4.636] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[1000] rmse=0.021510 lr=0.377098 +[1,0]:INFO:root:Epoch[45] Batch[1100] Loss[3.025] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[1100] rmse=0.021522 lr=0.377010 +[1,0]:INFO:root:Epoch[45] Batch[1200] Loss[3.111] +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[1200] rmse=0.021530 lr=0.376922 +[1,0]:INFO:root:Epoch[45] Rank[0] Batch[1251] Time cost=401.76 Train-metric=0.021539 +[1,0]:INFO:root:Epoch[45] Speed: 3188.54 samples/sec +[1,0]:INFO:root:Epoch[46] Batch[100] Loss[3.287] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[100] rmse=0.021619 lr=0.376788 +[1,0]:INFO:root:Epoch[46] Batch[200] Loss[2.989] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[200] rmse=0.021562 lr=0.376700 +[1,0]:INFO:root:Epoch[46] Batch[300] Loss[2.953] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[300] rmse=0.021494 lr=0.376611 +[1,0]:INFO:root:Epoch[46] Batch[400] Loss[3.285] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[400] rmse=0.021470 lr=0.376522 +[1,0]:INFO:root:Epoch[46] Batch[500] Loss[2.985] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[500] rmse=0.021423 lr=0.376433 +[1,0]:INFO:root:Epoch[46] Batch[600] Loss[2.977] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[600] rmse=0.021443 lr=0.376344 +[1,0]:INFO:root:Epoch[46] Batch[700] Loss[3.409] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[700] rmse=0.021462 lr=0.376254 +[1,0]:INFO:root:Epoch[46] Batch[800] Loss[3.309] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[800] rmse=0.021468 lr=0.376165 +[1,0]:INFO:root:Epoch[46] Batch[900] Loss[5.404] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[900] rmse=0.021460 lr=0.376075 +[1,0]:INFO:root:Epoch[46] Batch[1000] Loss[3.478] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[1000] rmse=0.021467 lr=0.375985 +[1,0]:INFO:root:Epoch[46] Batch[1100] Loss[2.819] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[1100] rmse=0.021467 lr=0.375895 +[1,0]:INFO:root:Epoch[46] Batch[1200] Loss[2.872] +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[1200] rmse=0.021461 lr=0.375805 +[1,0]:INFO:root:Epoch[46] Rank[0] Batch[1251] Time cost=399.89 Train-metric=0.021458 +[1,0]:INFO:root:Epoch[46] Speed: 3203.41 samples/sec +[1,0]:INFO:root:Epoch[47] Batch[100] Loss[2.889] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[100] rmse=0.021394 lr=0.375668 +[1,0]:INFO:root:Epoch[47] Batch[200] Loss[3.033] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[200] rmse=0.021405 lr=0.375578 +[1,0]:INFO:root:Epoch[47] Batch[300] Loss[3.407] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[300] rmse=0.021360 lr=0.375487 +[1,0]:INFO:root:Epoch[47] Batch[400] Loss[3.249] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[400] rmse=0.021469 lr=0.375396 +[1,0]:INFO:root:Epoch[47] Batch[500] Loss[3.583] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[500] rmse=0.021469 lr=0.375305 +[1,0]:INFO:root:Epoch[47] Batch[600] Loss[3.115] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[600] rmse=0.021438 lr=0.375214 +[1,0]:INFO:root:Epoch[47] Batch[700] Loss[3.313] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[700] rmse=0.021469 lr=0.375122 +[1,0]:INFO:root:Epoch[47] Batch[800] Loss[5.394] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[800] rmse=0.021456 lr=0.375031 +[1,0]:INFO:root:Epoch[47] Batch[900] Loss[3.361] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[900] rmse=0.021452 lr=0.374939 +[1,0]:INFO:root:Epoch[47] Batch[1000] Loss[2.930] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[1000] rmse=0.021473 lr=0.374847 +[1,0]:INFO:root:Epoch[47] Batch[1100] Loss[5.359] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[1100] rmse=0.021450 lr=0.374755 +[1,0]:INFO:root:Epoch[47] Batch[1200] Loss[3.957] +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[1200] rmse=0.021451 lr=0.374663 +[1,0]:INFO:root:Epoch[47] Rank[0] Batch[1251] Time cost=400.99 Train-metric=0.021450 +[1,0]:INFO:root:Epoch[47] Speed: 3194.64 samples/sec +[1,0]:INFO:root:Epoch[48] Batch[100] Loss[5.597] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[100] rmse=0.021429 lr=0.374523 +[1,0]:INFO:root:Epoch[48] Batch[200] Loss[3.221] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[200] rmse=0.021416 lr=0.374431 +[1,0]:INFO:root:Epoch[48] Batch[300] Loss[3.159] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[300] rmse=0.021405 lr=0.374338 +[1,0]:INFO:root:Epoch[48] Batch[400] Loss[5.407] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[400] rmse=0.021393 lr=0.374245 +[1,0]:INFO:root:Epoch[48] Batch[500] Loss[3.365] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[500] rmse=0.021391 lr=0.374152 +[1,0]:INFO:root:Epoch[48] Batch[600] Loss[3.179] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[600] rmse=0.021397 lr=0.374059 +[1,0]:INFO:root:Epoch[48] Batch[700] Loss[3.207] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[700] rmse=0.021427 lr=0.373966 +[1,0]:INFO:root:Epoch[48] Batch[800] Loss[3.164] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[800] rmse=0.021408 lr=0.373872 +[1,0]:INFO:root:Epoch[48] Batch[900] Loss[3.408] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[900] rmse=0.021408 lr=0.373779 +[1,0]:INFO:root:Epoch[48] Batch[1000] Loss[3.332] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[1000] rmse=0.021434 lr=0.373685 +[1,0]:INFO:root:Epoch[48] Batch[1100] Loss[3.193] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[1100] rmse=0.021445 lr=0.373591 +[1,0]:INFO:root:Epoch[48] Batch[1200] Loss[2.761] +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[1200] rmse=0.021445 lr=0.373497 +[1,0]:INFO:root:Epoch[48] Rank[0] Batch[1251] Time cost=399.09 Train-metric=0.021440 +[1,0]:INFO:root:Epoch[48] Speed: 3209.86 samples/sec +[1,0]:INFO:root:Epoch[49] Batch[100] Loss[2.995] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[100] rmse=0.021526 lr=0.373354 +[1,0]:INFO:root:Epoch[49] Batch[200] Loss[3.143] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[200] rmse=0.021344 lr=0.373260 +[1,0]:INFO:root:Epoch[49] Batch[300] Loss[3.390] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[300] rmse=0.021314 lr=0.373165 +[1,0]:INFO:root:Epoch[49] Batch[400] Loss[3.693] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[400] rmse=0.021277 lr=0.373070 +[1,0]:INFO:root:Epoch[49] Batch[500] Loss[2.969] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[500] rmse=0.021337 lr=0.372975 +[1,0]:INFO:root:Epoch[49] Batch[600] Loss[3.016] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[600] rmse=0.021336 lr=0.372880 +[1,0]:INFO:root:Epoch[49] Batch[700] Loss[4.827] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[700] rmse=0.021363 lr=0.372785 +[1,0]:INFO:root:Epoch[49] Batch[800] Loss[3.006] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[800] rmse=0.021361 lr=0.372689 +[1,0]:INFO:root:Epoch[49] Batch[900] Loss[3.194] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[900] rmse=0.021399 lr=0.372594 +[1,0]:INFO:root:Epoch[49] Batch[1000] Loss[4.188] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[1000] rmse=0.021424 lr=0.372498 +[1,0]:INFO:root:Epoch[49] Batch[1100] Loss[3.034] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[1100] rmse=0.021424 lr=0.372402 +[1,0]:INFO:root:Epoch[49] Batch[1200] Loss[2.904] +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[1200] rmse=0.021448 lr=0.372306 +[1,0]:INFO:root:Epoch[49] Rank[0] Batch[1251] Time cost=398.81 Train-metric=0.021458 +[1,0]:INFO:root:Epoch[49] Speed: 3212.13 samples/sec +[1,0]:INFO:root:Epoch[49] Rank[0] Validation-accuracy=0.559560 Validation-top_k_accuracy_5=0.803140 +[1,0]:INFO:root:Epoch[50] Batch[100] Loss[4.187] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[100] rmse=0.021244 lr=0.372161 +[1,0]:INFO:root:Epoch[50] Batch[200] Loss[2.888] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[200] rmse=0.021419 lr=0.372064 +[1,0]:INFO:root:Epoch[50] Batch[300] Loss[3.508] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[300] rmse=0.021350 lr=0.371967 +[1,0]:INFO:root:Epoch[50] Batch[400] Loss[2.932] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[400] rmse=0.021356 lr=0.371871 +[1,0]:INFO:root:Epoch[50] Batch[500] Loss[2.681] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[500] rmse=0.021370 lr=0.371774 +[1,0]:INFO:root:Epoch[50] Batch[600] Loss[4.528] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[600] rmse=0.021372 lr=0.371677 +[1,0]:INFO:root:Epoch[50] Batch[700] Loss[2.739] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[700] rmse=0.021392 lr=0.371579 +[1,0]:INFO:root:Epoch[50] Batch[800] Loss[3.713] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[800] rmse=0.021392 lr=0.371482 +[1,0]:INFO:root:Epoch[50] Batch[900] Loss[4.326] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[900] rmse=0.021384 lr=0.371385 +[1,0]:INFO:root:Epoch[50] Batch[1000] Loss[3.005] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[1000] rmse=0.021413 lr=0.371287 +[1,0]:INFO:root:Epoch[50] Batch[1100] Loss[3.070] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[1100] rmse=0.021432 lr=0.371189 +[1,0]:INFO:root:Epoch[50] Batch[1200] Loss[3.900] +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[1200] rmse=0.021465 lr=0.371091 +[1,0]:INFO:root:Epoch[50] Rank[0] Batch[1251] Time cost=398.02 Train-metric=0.021468 +[1,0]:INFO:root:Epoch[50] Speed: 3218.52 samples/sec +[1,0]:INFO:root:Epoch[51] Batch[100] Loss[2.760] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[100] rmse=0.021453 lr=0.370943 +[1,0]:INFO:root:Epoch[51] Batch[200] Loss[5.153] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[200] rmse=0.021375 lr=0.370844 +[1,0]:INFO:root:Epoch[51] Batch[300] Loss[3.499] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[300] rmse=0.021428 lr=0.370746 +[1,0]:INFO:root:Epoch[51] Batch[400] Loss[2.961] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[400] rmse=0.021423 lr=0.370647 +[1,0]:INFO:root:Epoch[51] Batch[500] Loss[4.979] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[500] rmse=0.021422 lr=0.370548 +[1,0]:INFO:root:Epoch[51] Batch[600] Loss[3.580] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[600] rmse=0.021444 lr=0.370449 +[1,0]:INFO:root:Epoch[51] Batch[700] Loss[2.961] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[700] rmse=0.021472 lr=0.370350 +[1,0]:INFO:root:Epoch[51] Batch[800] Loss[2.974] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[800] rmse=0.021463 lr=0.370251 +[1,0]:INFO:root:Epoch[51] Batch[900] Loss[2.937] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[900] rmse=0.021477 lr=0.370151 +[1,0]:INFO:root:Epoch[51] Batch[1000] Loss[3.612] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[1000] rmse=0.021494 lr=0.370052 +[1,0]:INFO:root:Epoch[51] Batch[1100] Loss[2.980] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[1100] rmse=0.021489 lr=0.369952 +[1,0]:INFO:root:Epoch[51] Batch[1200] Loss[4.338] +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[1200] rmse=0.021486 lr=0.369852 +[1,0]:INFO:root:Epoch[51] Rank[0] Batch[1251] Time cost=399.30 Train-metric=0.021483 +[1,0]:INFO:root:Epoch[51] Speed: 3208.14 samples/sec +[1,0]:INFO:root:Epoch[52] Batch[100] Loss[5.323] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[100] rmse=0.021240 lr=0.369701 +[1,0]:INFO:root:Epoch[52] Batch[200] Loss[3.812] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[200] rmse=0.021346 lr=0.369601 +[1,0]:INFO:root:Epoch[52] Batch[300] Loss[2.935] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[300] rmse=0.021372 lr=0.369500 +[1,0]:INFO:root:Epoch[52] Batch[400] Loss[3.090] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[400] rmse=0.021400 lr=0.369400 +[1,0]:INFO:root:Epoch[52] Batch[500] Loss[4.143] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[500] rmse=0.021414 lr=0.369299 +[1,0]:INFO:root:Epoch[52] Batch[600] Loss[2.985] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[600] rmse=0.021437 lr=0.369198 +[1,0]:INFO:root:Epoch[52] Batch[700] Loss[3.073] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[700] rmse=0.021437 lr=0.369097 +[1,0]:INFO:root:Epoch[52] Batch[800] Loss[2.866] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[800] rmse=0.021410 lr=0.368996 +[1,0]:INFO:root:Epoch[52] Batch[900] Loss[3.232] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[900] rmse=0.021409 lr=0.368894 +[1,0]:INFO:root:Epoch[52] Batch[1000] Loss[2.910] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[1000] rmse=0.021395 lr=0.368793 +[1,0]:INFO:root:Epoch[52] Batch[1100] Loss[3.109] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[1100] rmse=0.021408 lr=0.368691 +[1,0]:INFO:root:Epoch[52] Batch[1200] Loss[3.235] +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[1200] rmse=0.021415 lr=0.368589 +[1,0]:INFO:root:Epoch[52] Rank[0] Batch[1251] Time cost=400.41 Train-metric=0.021414 +[1,0]:INFO:root:Epoch[52] Speed: 3199.31 samples/sec +[1,0]:INFO:root:Epoch[53] Batch[100] Loss[3.150] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[100] rmse=0.021228 lr=0.368435 +[1,0]:INFO:root:Epoch[53] Batch[200] Loss[3.012] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[200] rmse=0.021246 lr=0.368333 +[1,0]:INFO:root:Epoch[53] Batch[300] Loss[2.943] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[300] rmse=0.021248 lr=0.368231 +[1,0]:INFO:root:Epoch[53] Batch[400] Loss[2.799] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[400] rmse=0.021259 lr=0.368128 +[1,0]:INFO:root:Epoch[53] Batch[500] Loss[2.981] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[500] rmse=0.021322 lr=0.368026 +[1,0]:INFO:root:Epoch[53] Batch[600] Loss[4.510] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[600] rmse=0.021356 lr=0.367923 +[1,0]:INFO:root:Epoch[53] Batch[700] Loss[2.966] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[700] rmse=0.021371 lr=0.367820 +[1,0]:INFO:root:Epoch[53] Batch[800] Loss[2.694] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[800] rmse=0.021404 lr=0.367717 +[1,0]:INFO:root:Epoch[53] Batch[900] Loss[3.332] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[900] rmse=0.021415 lr=0.367614 +[1,0]:INFO:root:Epoch[53] Batch[1000] Loss[5.288] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[1000] rmse=0.021427 lr=0.367510 +[1,0]:INFO:root:Epoch[53] Batch[1100] Loss[4.044] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[1100] rmse=0.021426 lr=0.367407 +[1,0]:INFO:root:Epoch[53] Batch[1200] Loss[3.047] +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[1200] rmse=0.021431 lr=0.367303 +[1,0]:INFO:root:Epoch[53] Rank[0] Batch[1251] Time cost=399.45 Train-metric=0.021420 +[1,0]:INFO:root:Epoch[53] Speed: 3206.94 samples/sec +[1,0]:INFO:root:Epoch[54] Batch[100] Loss[3.494] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[100] rmse=0.021105 lr=0.367146 +[1,0]:INFO:root:Epoch[54] Batch[200] Loss[3.101] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[200] rmse=0.021275 lr=0.367042 +[1,0]:INFO:root:Epoch[54] Batch[300] Loss[3.000] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[300] rmse=0.021321 lr=0.366938 +[1,0]:INFO:root:Epoch[54] Batch[400] Loss[2.786] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[400] rmse=0.021318 lr=0.366834 +[1,0]:INFO:root:Epoch[54] Batch[500] Loss[2.781] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[500] rmse=0.021368 lr=0.366729 +[1,0]:INFO:root:Epoch[54] Batch[600] Loss[2.730] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[600] rmse=0.021381 lr=0.366624 +[1,0]:INFO:root:Epoch[54] Batch[700] Loss[3.842] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[700] rmse=0.021409 lr=0.366520 +[1,0]:INFO:root:Epoch[54] Batch[800] Loss[2.861] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[800] rmse=0.021406 lr=0.366415 +[1,0]:INFO:root:Epoch[54] Batch[900] Loss[3.286] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[900] rmse=0.021408 lr=0.366309 +[1,0]:INFO:root:Epoch[54] Batch[1000] Loss[3.896] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[1000] rmse=0.021407 lr=0.366204 +[1,0]:INFO:root:Epoch[54] Batch[1100] Loss[4.758] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[1100] rmse=0.021405 lr=0.366099 +[1,0]:INFO:root:Epoch[54] Batch[1200] Loss[4.291] +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[1200] rmse=0.021411 lr=0.365993 +[1,0]:INFO:root:Epoch[54] Rank[0] Batch[1251] Time cost=399.09 Train-metric=0.021410 +[1,0]:INFO:root:Epoch[54] Speed: 3209.84 samples/sec +[1,0]:INFO:root:Epoch[54] Rank[0] Validation-accuracy=0.574500 Validation-top_k_accuracy_5=0.817740 +[1,0]:INFO:root:Epoch[55] Batch[100] Loss[3.326] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[100] rmse=0.021402 lr=0.365834 +[1,0]:INFO:root:Epoch[55] Batch[200] Loss[2.659] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[200] rmse=0.021429 lr=0.365728 +[1,0]:INFO:root:Epoch[55] Batch[300] Loss[3.375] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[300] rmse=0.021426 lr=0.365621 +[1,0]:INFO:root:Epoch[55] Batch[400] Loss[3.161] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[400] rmse=0.021417 lr=0.365515 +[1,0]:INFO:root:Epoch[55] Batch[500] Loss[3.356] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[500] rmse=0.021462 lr=0.365409 +[1,0]:INFO:root:Epoch[55] Batch[600] Loss[2.820] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[600] rmse=0.021462 lr=0.365302 +[1,0]:INFO:root:Epoch[55] Batch[700] Loss[3.510] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[700] rmse=0.021444 lr=0.365196 +[1,0]:INFO:root:Epoch[55] Batch[800] Loss[3.459] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[800] rmse=0.021457 lr=0.365089 +[1,0]:INFO:root:Epoch[55] Batch[900] Loss[3.194] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[900] rmse=0.021428 lr=0.364982 +[1,0]:INFO:root:Epoch[55] Batch[1000] Loss[5.408] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[1000] rmse=0.021445 lr=0.364875 +[1,0]:INFO:root:Epoch[55] Batch[1100] Loss[4.200] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[1100] rmse=0.021459 lr=0.364767 +[1,0]:INFO:root:Epoch[55] Batch[1200] Loss[3.078] +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[1200] rmse=0.021449 lr=0.364660 +[1,0]:INFO:root:Epoch[55] Rank[0] Batch[1251] Time cost=398.13 Train-metric=0.021463 +[1,0]:INFO:root:Epoch[55] Speed: 3217.59 samples/sec +[1,0]:INFO:root:Epoch[56] Batch[100] Loss[3.431] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[100] rmse=0.021501 lr=0.364498 +[1,0]:INFO:root:Epoch[56] Batch[200] Loss[4.922] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[200] rmse=0.021337 lr=0.364390 +[1,0]:INFO:root:Epoch[56] Batch[300] Loss[4.310] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[300] rmse=0.021301 lr=0.364282 +[1,0]:INFO:root:Epoch[56] Batch[400] Loss[3.055] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[400] rmse=0.021360 lr=0.364174 +[1,0]:INFO:root:Epoch[56] Batch[500] Loss[3.255] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[500] rmse=0.021342 lr=0.364066 +[1,0]:INFO:root:Epoch[56] Batch[600] Loss[3.059] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[600] rmse=0.021350 lr=0.363957 +[1,0]:INFO:root:Epoch[56] Batch[700] Loss[2.831] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[700] rmse=0.021382 lr=0.363849 +[1,0]:INFO:root:Epoch[56] Batch[800] Loss[3.433] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[800] rmse=0.021390 lr=0.363740 +[1,0]:INFO:root:Epoch[56] Batch[900] Loss[3.015] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[900] rmse=0.021403 lr=0.363631 +[1,0]:INFO:root:Epoch[56] Batch[1000] Loss[2.951] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[1000] rmse=0.021408 lr=0.363522 +[1,0]:INFO:root:Epoch[56] Batch[1100] Loss[3.184] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[1100] rmse=0.021423 lr=0.363413 +[1,0]:INFO:root:Epoch[56] Batch[1200] Loss[5.117] +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[1200] rmse=0.021422 lr=0.363304 +[1,0]:INFO:root:Epoch[56] Rank[0] Batch[1251] Time cost=399.77 Train-metric=0.021427 +[1,0]:INFO:root:Epoch[56] Speed: 3204.37 samples/sec +[1,0]:INFO:root:Epoch[57] Batch[100] Loss[3.545] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[100] rmse=0.021303 lr=0.363139 +[1,0]:INFO:root:Epoch[57] Batch[200] Loss[4.619] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[200] rmse=0.021364 lr=0.363029 +[1,0]:INFO:root:Epoch[57] Batch[300] Loss[3.832] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[300] rmse=0.021396 lr=0.362919 +[1,0]:INFO:root:Epoch[57] Batch[400] Loss[3.274] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[400] rmse=0.021432 lr=0.362809 +[1,0]:INFO:root:Epoch[57] Batch[500] Loss[3.223] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[500] rmse=0.021478 lr=0.362699 +[1,0]:INFO:root:Epoch[57] Batch[600] Loss[5.003] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[600] rmse=0.021448 lr=0.362589 +[1,0]:INFO:root:Epoch[57] Batch[700] Loss[3.111] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[700] rmse=0.021464 lr=0.362479 +[1,0]:INFO:root:Epoch[57] Batch[800] Loss[2.980] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[800] rmse=0.021464 lr=0.362368 +[1,0]:INFO:root:Epoch[57] Batch[900] Loss[3.786] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[900] rmse=0.021463 lr=0.362257 +[1,0]:INFO:root:Epoch[57] Batch[1000] Loss[3.056] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[1000] rmse=0.021461 lr=0.362147 +[1,0]:INFO:root:Epoch[57] Batch[1100] Loss[3.055] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[1100] rmse=0.021457 lr=0.362036 +[1,0]:INFO:root:Epoch[57] Batch[1200] Loss[5.030] +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[1200] rmse=0.021426 lr=0.361925 +[1,0]:INFO:root:Epoch[57] Rank[0] Batch[1251] Time cost=398.82 Train-metric=0.021414 +[1,0]:INFO:root:Epoch[57] Speed: 3212.04 samples/sec +[1,0]:INFO:root:Epoch[58] Batch[100] Loss[2.821] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[100] rmse=0.021200 lr=0.361757 +[1,0]:INFO:root:Epoch[58] Batch[200] Loss[2.828] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[200] rmse=0.021227 lr=0.361645 +[1,0]:INFO:root:Epoch[58] Batch[300] Loss[3.512] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[300] rmse=0.021245 lr=0.361534 +[1,0]:INFO:root:Epoch[58] Batch[400] Loss[3.224] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[400] rmse=0.021320 lr=0.361422 +[1,0]:INFO:root:Epoch[58] Batch[500] Loss[3.170] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[500] rmse=0.021330 lr=0.361310 +[1,0]:INFO:root:Epoch[58] Batch[600] Loss[3.089] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[600] rmse=0.021303 lr=0.361198 +[1,0]:INFO:root:Epoch[58] Batch[700] Loss[3.276] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[700] rmse=0.021340 lr=0.361086 +[1,0]:INFO:root:Epoch[58] Batch[800] Loss[4.920] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[800] rmse=0.021333 lr=0.360973 +[1,0]:INFO:root:Epoch[58] Batch[900] Loss[3.149] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[900] rmse=0.021364 lr=0.360861 +[1,0]:INFO:root:Epoch[58] Batch[1000] Loss[2.859] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[1000] rmse=0.021354 lr=0.360748 +[1,0]:INFO:root:Epoch[58] Batch[1100] Loss[2.819] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[1100] rmse=0.021372 lr=0.360636 +[1,0]:INFO:root:Epoch[58] Batch[1200] Loss[3.076] +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[1200] rmse=0.021390 lr=0.360523 +[1,0]:INFO:root:Epoch[58] Rank[0] Batch[1251] Time cost=400.37 Train-metric=0.021412 +[1,0]:INFO:root:Epoch[58] Speed: 3199.58 samples/sec +[1,0]:INFO:root:Epoch[59] Batch[100] Loss[2.911] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[100] rmse=0.021265 lr=0.360352 +[1,0]:INFO:root:Epoch[59] Batch[200] Loss[4.113] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[200] rmse=0.021257 lr=0.360239 +[1,0]:INFO:root:Epoch[59] Batch[300] Loss[3.808] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[300] rmse=0.021247 lr=0.360125 +[1,0]:INFO:root:Epoch[59] Batch[400] Loss[3.013] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[400] rmse=0.021198 lr=0.360012 +[1,0]:INFO:root:Epoch[59] Batch[500] Loss[5.018] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[500] rmse=0.021209 lr=0.359898 +[1,0]:INFO:root:Epoch[59] Batch[600] Loss[3.308] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[600] rmse=0.021236 lr=0.359784 +[1,0]:INFO:root:Epoch[59] Batch[700] Loss[2.795] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[700] rmse=0.021277 lr=0.359670 +[1,0]:INFO:root:Epoch[59] Batch[800] Loss[4.162] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[800] rmse=0.021282 lr=0.359556 +[1,0]:INFO:root:Epoch[59] Batch[900] Loss[3.241] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[900] rmse=0.021304 lr=0.359442 +[1,0]:INFO:root:Epoch[59] Batch[1000] Loss[4.570] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[1000] rmse=0.021317 lr=0.359328 +[1,0]:INFO:root:Epoch[59] Batch[1100] Loss[3.232] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[1100] rmse=0.021333 lr=0.359213 +[1,0]:INFO:root:Epoch[59] Batch[1200] Loss[4.192] +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[1200] rmse=0.021332 lr=0.359098 +[1,0]:INFO:root:Epoch[59] Rank[0] Batch[1251] Time cost=399.21 Train-metric=0.021328 +[1,0]:INFO:root:Epoch[59] Speed: 3208.92 samples/sec +[1,0]:INFO:root:Epoch[59] Rank[0] Validation-accuracy=0.556400 Validation-top_k_accuracy_5=0.801860 +[1,0]:INFO:root:Epoch[60] Batch[100] Loss[3.155] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[100] rmse=0.021360 lr=0.358925 +[1,0]:INFO:root:Epoch[60] Batch[200] Loss[4.769] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[200] rmse=0.021251 lr=0.358810 +[1,0]:INFO:root:Epoch[60] Batch[300] Loss[3.065] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[300] rmse=0.021256 lr=0.358695 +[1,0]:INFO:root:Epoch[60] Batch[400] Loss[5.331] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[400] rmse=0.021224 lr=0.358579 +[1,0]:INFO:root:Epoch[60] Batch[500] Loss[5.443] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[500] rmse=0.021249 lr=0.358464 +[1,0]:INFO:root:Epoch[60] Batch[600] Loss[3.131] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[600] rmse=0.021286 lr=0.358348 +[1,0]:INFO:root:Epoch[60] Batch[700] Loss[3.459] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[700] rmse=0.021319 lr=0.358233 +[1,0]:INFO:root:Epoch[60] Batch[800] Loss[3.142] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[800] rmse=0.021335 lr=0.358117 +[1,0]:INFO:root:Epoch[60] Batch[900] Loss[3.263] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[900] rmse=0.021330 lr=0.358001 +[1,0]:INFO:root:Epoch[60] Batch[1000] Loss[3.634] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[1000] rmse=0.021326 lr=0.357884 +[1,0]:INFO:root:Epoch[60] Batch[1100] Loss[3.191] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[1100] rmse=0.021351 lr=0.357768 +[1,0]:INFO:root:Epoch[60] Batch[1200] Loss[3.449] +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[1200] rmse=0.021359 lr=0.357652 +[1,0]:INFO:root:Epoch[60] Rank[0] Batch[1251] Time cost=399.37 Train-metric=0.021361 +[1,0]:INFO:root:Epoch[60] Speed: 3207.63 samples/sec +[1,0]:INFO:root:Epoch[61] Batch[100] Loss[3.552] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[100] rmse=0.021141 lr=0.357475 +[1,0]:INFO:root:Epoch[61] Batch[200] Loss[3.986] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[200] rmse=0.021239 lr=0.357359 +[1,0]:INFO:root:Epoch[61] Batch[300] Loss[3.646] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[300] rmse=0.021225 lr=0.357242 +[1,0]:INFO:root:Epoch[61] Batch[400] Loss[3.115] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[400] rmse=0.021240 lr=0.357125 +[1,0]:INFO:root:Epoch[61] Batch[500] Loss[4.354] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[500] rmse=0.021254 lr=0.357007 +[1,0]:INFO:root:Epoch[61] Batch[600] Loss[3.433] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[600] rmse=0.021308 lr=0.356890 +[1,0]:INFO:root:Epoch[61] Batch[700] Loss[2.916] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[700] rmse=0.021348 lr=0.356772 +[1,0]:INFO:root:Epoch[61] Batch[800] Loss[4.002] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[800] rmse=0.021361 lr=0.356655 +[1,0]:INFO:root:Epoch[61] Batch[900] Loss[2.850] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[900] rmse=0.021375 lr=0.356537 +[1,0]:INFO:root:Epoch[61] Batch[1000] Loss[3.160] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[1000] rmse=0.021372 lr=0.356419 +[1,0]:INFO:root:Epoch[61] Batch[1100] Loss[3.405] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[1100] rmse=0.021357 lr=0.356301 +[1,0]:INFO:root:Epoch[61] Batch[1200] Loss[3.861] +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[1200] rmse=0.021380 lr=0.356183 +[1,0]:INFO:root:Epoch[61] Rank[0] Batch[1251] Time cost=399.14 Train-metric=0.021382 +[1,0]:INFO:root:Epoch[61] Speed: 3209.44 samples/sec +[1,0]:INFO:root:Epoch[62] Batch[100] Loss[2.955] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[100] rmse=0.021346 lr=0.356004 +[1,0]:INFO:root:Epoch[62] Batch[200] Loss[3.860] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[200] rmse=0.021232 lr=0.355885 +[1,0]:INFO:root:Epoch[62] Batch[300] Loss[4.532] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[300] rmse=0.021270 lr=0.355767 +[1,0]:INFO:root:Epoch[62] Batch[400] Loss[3.216] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[400] rmse=0.021282 lr=0.355648 +[1,0]:INFO:root:Epoch[62] Batch[500] Loss[5.358] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[500] rmse=0.021279 lr=0.355529 +[1,0]:INFO:root:Epoch[62] Batch[600] Loss[3.165] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[600] rmse=0.021279 lr=0.355410 +[1,0]:INFO:root:Epoch[62] Batch[700] Loss[3.186] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[700] rmse=0.021305 lr=0.355290 +[1,0]:INFO:root:Epoch[62] Batch[800] Loss[3.294] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[800] rmse=0.021346 lr=0.355171 +[1,0]:INFO:root:Epoch[62] Batch[900] Loss[4.868] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[900] rmse=0.021350 lr=0.355051 +[1,0]:INFO:root:Epoch[62] Batch[1000] Loss[3.553] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[1000] rmse=0.021311 lr=0.354932 +[1,0]:INFO:root:Epoch[62] Batch[1100] Loss[3.015] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[1100] rmse=0.021329 lr=0.354812 +[1,0]:INFO:root:Epoch[62] Batch[1200] Loss[2.970] +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[1200] rmse=0.021333 lr=0.354692 +[1,0]:INFO:root:Epoch[62] Rank[0] Batch[1251] Time cost=399.11 Train-metric=0.021349 +[1,0]:INFO:root:Epoch[62] Speed: 3209.71 samples/sec +[1,0]:INFO:root:Epoch[63] Batch[100] Loss[2.987] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[100] rmse=0.021450 lr=0.354511 +[1,0]:INFO:root:Epoch[63] Batch[200] Loss[3.088] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[200] rmse=0.021398 lr=0.354390 +[1,0]:INFO:root:Epoch[63] Batch[300] Loss[3.077] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[300] rmse=0.021382 lr=0.354270 +[1,0]:INFO:root:Epoch[63] Batch[400] Loss[3.089] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[400] rmse=0.021372 lr=0.354149 +[1,0]:INFO:root:Epoch[63] Batch[500] Loss[3.293] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[500] rmse=0.021340 lr=0.354029 +[1,0]:INFO:root:Epoch[63] Batch[600] Loss[5.331] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[600] rmse=0.021351 lr=0.353908 +[1,0]:INFO:root:Epoch[63] Batch[700] Loss[4.569] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[700] rmse=0.021356 lr=0.353787 +[1,0]:INFO:root:Epoch[63] Batch[800] Loss[2.890] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[800] rmse=0.021367 lr=0.353665 +[1,0]:INFO:root:Epoch[63] Batch[900] Loss[3.320] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[900] rmse=0.021340 lr=0.353544 +[1,0]:INFO:root:Epoch[63] Batch[1000] Loss[5.166] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[1000] rmse=0.021334 lr=0.353423 +[1,0]:INFO:root:Epoch[63] Batch[1100] Loss[2.758] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[1100] rmse=0.021327 lr=0.353301 +[1,0]:INFO:root:Epoch[63] Batch[1200] Loss[4.872] +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[1200] rmse=0.021337 lr=0.353180 +[1,0]:INFO:root:Epoch[63] Rank[0] Batch[1251] Time cost=398.61 Train-metric=0.021334 +[1,0]:INFO:root:Epoch[63] Speed: 3213.71 samples/sec +[1,0]:INFO:root:Epoch[64] Batch[100] Loss[2.982] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[100] rmse=0.021226 lr=0.352996 +[1,0]:INFO:root:Epoch[64] Batch[200] Loss[5.034] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[200] rmse=0.021215 lr=0.352873 +[1,0]:INFO:root:Epoch[64] Batch[300] Loss[3.123] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[300] rmse=0.021238 lr=0.352751 +[1,0]:INFO:root:Epoch[64] Batch[400] Loss[5.342] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[400] rmse=0.021219 lr=0.352629 +[1,0]:INFO:root:Epoch[64] Batch[500] Loss[4.914] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[500] rmse=0.021255 lr=0.352507 +[1,0]:INFO:root:Epoch[64] Batch[600] Loss[2.806] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[600] rmse=0.021281 lr=0.352384 +[1,0]:INFO:root:Epoch[64] Batch[700] Loss[2.832] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[700] rmse=0.021264 lr=0.352261 +[1,0]:INFO:root:Epoch[64] Batch[800] Loss[4.591] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[800] rmse=0.021287 lr=0.352138 +[1,0]:INFO:root:Epoch[64] Batch[900] Loss[3.012] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[900] rmse=0.021315 lr=0.352015 +[1,0]:INFO:root:Epoch[64] Batch[1000] Loss[3.834] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[1000] rmse=0.021329 lr=0.351892 +[1,0]:INFO:root:Epoch[64] Batch[1100] Loss[4.093] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[1100] rmse=0.021333 lr=0.351769 +[1,0]:INFO:root:Epoch[64] Batch[1200] Loss[5.034] +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[1200] rmse=0.021346 lr=0.351646 +[1,0]:INFO:root:Epoch[64] Rank[0] Batch[1251] Time cost=398.93 Train-metric=0.021346 +[1,0]:INFO:root:Epoch[64] Speed: 3211.17 samples/sec +[1,0]:INFO:root:Epoch[64] Rank[0] Validation-accuracy=0.587840 Validation-top_k_accuracy_5=0.823020 +[1,0]:INFO:root:Epoch[65] Batch[100] Loss[3.222] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[100] rmse=0.021190 lr=0.351459 +[1,0]:INFO:root:Epoch[65] Batch[200] Loss[2.901] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[200] rmse=0.021161 lr=0.351335 +[1,0]:INFO:root:Epoch[65] Batch[300] Loss[4.694] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[300] rmse=0.021233 lr=0.351211 +[1,0]:INFO:root:Epoch[65] Batch[400] Loss[3.470] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[400] rmse=0.021277 lr=0.351087 +[1,0]:INFO:root:Epoch[65] Batch[500] Loss[4.302] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[500] rmse=0.021274 lr=0.350963 +[1,0]:INFO:root:Epoch[65] Batch[600] Loss[3.953] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[600] rmse=0.021304 lr=0.350839 +[1,0]:INFO:root:Epoch[65] Batch[700] Loss[2.940] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[700] rmse=0.021320 lr=0.350714 +[1,0]:INFO:root:Epoch[65] Batch[800] Loss[3.611] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[800] rmse=0.021320 lr=0.350590 +[1,0]:INFO:root:Epoch[65] Batch[900] Loss[4.573] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[900] rmse=0.021313 lr=0.350465 +[1,0]:INFO:root:Epoch[65] Batch[1000] Loss[4.632] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[1000] rmse=0.021309 lr=0.350340 +[1,0]:INFO:root:Epoch[65] Batch[1100] Loss[5.208] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[1100] rmse=0.021330 lr=0.350215 +[1,0]:INFO:root:Epoch[65] Batch[1200] Loss[2.995] +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[1200] rmse=0.021331 lr=0.350090 +[1,0]:INFO:root:Epoch[65] Rank[0] Batch[1251] Time cost=399.33 Train-metric=0.021329 +[1,0]:INFO:root:Epoch[65] Speed: 3207.94 samples/sec +[1,0]:INFO:root:Epoch[66] Batch[100] Loss[3.528] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[100] rmse=0.021123 lr=0.349901 +[1,0]:INFO:root:Epoch[66] Batch[200] Loss[5.436] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[200] rmse=0.021089 lr=0.349776 +[1,0]:INFO:root:Epoch[66] Batch[300] Loss[3.007] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[300] rmse=0.021116 lr=0.349650 +[1,0]:INFO:root:Epoch[66] Batch[400] Loss[5.195] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[400] rmse=0.021180 lr=0.349524 +[1,0]:INFO:root:Epoch[66] Batch[500] Loss[3.628] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[500] rmse=0.021173 lr=0.349399 +[1,0]:INFO:root:Epoch[66] Batch[600] Loss[3.214] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[600] rmse=0.021191 lr=0.349273 +[1,0]:INFO:root:Epoch[66] Batch[700] Loss[4.199] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[700] rmse=0.021228 lr=0.349147 +[1,0]:INFO:root:Epoch[66] Batch[800] Loss[4.516] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[800] rmse=0.021232 lr=0.349020 +[1,0]:INFO:root:Epoch[66] Batch[900] Loss[4.603] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[900] rmse=0.021223 lr=0.348894 +[1,0]:INFO:root:Epoch[66] Batch[1000] Loss[3.082] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[1000] rmse=0.021220 lr=0.348767 +[1,0]:INFO:root:Epoch[66] Batch[1100] Loss[5.140] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[1100] rmse=0.021232 lr=0.348641 +[1,0]:INFO:root:Epoch[66] Batch[1200] Loss[4.200] +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[1200] rmse=0.021255 lr=0.348514 +[1,0]:INFO:root:Epoch[66] Rank[0] Batch[1251] Time cost=398.66 Train-metric=0.021269 +[1,0]:INFO:root:Epoch[66] Speed: 3213.30 samples/sec +[1,0]:INFO:root:Epoch[67] Batch[100] Loss[3.276] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[100] rmse=0.021279 lr=0.348322 +[1,0]:INFO:root:Epoch[67] Batch[200] Loss[4.205] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[200] rmse=0.021301 lr=0.348195 +[1,0]:INFO:root:Epoch[67] Batch[300] Loss[3.440] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[300] rmse=0.021264 lr=0.348068 +[1,0]:INFO:root:Epoch[67] Batch[400] Loss[3.153] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[400] rmse=0.021274 lr=0.347941 +[1,0]:INFO:root:Epoch[67] Batch[500] Loss[4.841] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[500] rmse=0.021271 lr=0.347813 +[1,0]:INFO:root:Epoch[67] Batch[600] Loss[2.965] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[600] rmse=0.021285 lr=0.347685 +[1,0]:INFO:root:Epoch[67] Batch[700] Loss[5.435] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[700] rmse=0.021289 lr=0.347558 +[1,0]:INFO:root:Epoch[67] Batch[800] Loss[3.079] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[800] rmse=0.021292 lr=0.347430 +[1,0]:INFO:root:Epoch[67] Batch[900] Loss[3.201] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[900] rmse=0.021311 lr=0.347302 +[1,0]:INFO:root:Epoch[67] Batch[1000] Loss[5.390] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[1000] rmse=0.021309 lr=0.347174 +[1,0]:INFO:root:Epoch[67] Batch[1100] Loss[4.223] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[1100] rmse=0.021308 lr=0.347045 +[1,0]:INFO:root:Epoch[67] Batch[1200] Loss[3.049] +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[1200] rmse=0.021320 lr=0.346917 +[1,0]:INFO:root:Epoch[67] Rank[0] Batch[1251] Time cost=399.24 Train-metric=0.021314 +[1,0]:INFO:root:Epoch[67] Speed: 3208.64 samples/sec +[1,0]:INFO:root:Epoch[68] Batch[100] Loss[3.093] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[100] rmse=0.021109 lr=0.346723 +[1,0]:INFO:root:Epoch[68] Batch[200] Loss[3.422] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[200] rmse=0.021265 lr=0.346594 +[1,0]:INFO:root:Epoch[68] Batch[300] Loss[4.928] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[300] rmse=0.021353 lr=0.346465 +[1,0]:INFO:root:Epoch[68] Batch[400] Loss[2.947] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[400] rmse=0.021342 lr=0.346336 +[1,0]:INFO:root:Epoch[68] Batch[500] Loss[5.116] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[500] rmse=0.021278 lr=0.346207 +[1,0]:INFO:root:Epoch[68] Batch[600] Loss[2.848] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[600] rmse=0.021275 lr=0.346078 +[1,0]:INFO:root:Epoch[68] Batch[700] Loss[2.993] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[700] rmse=0.021263 lr=0.345948 +[1,0]:INFO:root:Epoch[68] Batch[800] Loss[3.255] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[800] rmse=0.021274 lr=0.345819 +[1,0]:INFO:root:Epoch[68] Batch[900] Loss[3.690] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[900] rmse=0.021303 lr=0.345689 +[1,0]:INFO:root:Epoch[68] Batch[1000] Loss[4.824] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[1000] rmse=0.021289 lr=0.345559 +[1,0]:INFO:root:Epoch[68] Batch[1100] Loss[2.946] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[1100] rmse=0.021280 lr=0.345429 +[1,0]:INFO:root:Epoch[68] Batch[1200] Loss[3.037] +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[1200] rmse=0.021265 lr=0.345299 +[1,0]:INFO:root:Epoch[68] Rank[0] Batch[1251] Time cost=400.88 Train-metric=0.021266 +[1,0]:INFO:root:Epoch[68] Speed: 3195.50 samples/sec +[1,0]:INFO:root:Epoch[69] Batch[100] Loss[3.196] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[100] rmse=0.021378 lr=0.345102 +[1,0]:INFO:root:Epoch[69] Batch[200] Loss[3.895] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[200] rmse=0.021290 lr=0.344972 +[1,0]:INFO:root:Epoch[69] Batch[300] Loss[3.527] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[300] rmse=0.021307 lr=0.344842 +[1,0]:INFO:root:Epoch[69] Batch[400] Loss[3.099] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[400] rmse=0.021281 lr=0.344711 +[1,0]:INFO:root:Epoch[69] Batch[500] Loss[3.071] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[500] rmse=0.021276 lr=0.344580 +[1,0]:INFO:root:Epoch[69] Batch[600] Loss[5.183] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[600] rmse=0.021281 lr=0.344449 +[1,0]:INFO:root:Epoch[69] Batch[700] Loss[5.385] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[700] rmse=0.021276 lr=0.344318 +[1,0]:INFO:root:Epoch[69] Batch[800] Loss[5.155] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[800] rmse=0.021296 lr=0.344187 +[1,0]:INFO:root:Epoch[69] Batch[900] Loss[3.066] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[900] rmse=0.021322 lr=0.344056 +[1,0]:INFO:root:Epoch[69] Batch[1000] Loss[4.413] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[1000] rmse=0.021325 lr=0.343924 +[1,0]:INFO:root:Epoch[69] Batch[1100] Loss[2.971] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[1100] rmse=0.021327 lr=0.343793 +[1,0]:INFO:root:Epoch[69] Batch[1200] Loss[3.079] +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[1200] rmse=0.021323 lr=0.343661 +[1,0]:INFO:root:Epoch[69] Rank[0] Batch[1251] Time cost=402.02 Train-metric=0.021322 +[1,0]:INFO:root:Epoch[69] Speed: 3186.47 samples/sec +[1,0]:INFO:root:Epoch[69] Rank[0] Validation-accuracy=0.591940 Validation-top_k_accuracy_5=0.828400 +[1,0]:INFO:root:Epoch[70] Batch[100] Loss[2.697] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[100] rmse=0.021141 lr=0.343462 +[1,0]:INFO:root:Epoch[70] Batch[200] Loss[3.745] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[200] rmse=0.021229 lr=0.343330 +[1,0]:INFO:root:Epoch[70] Batch[300] Loss[5.397] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[300] rmse=0.021204 lr=0.343198 +[1,0]:INFO:root:Epoch[70] Batch[400] Loss[3.114] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[400] rmse=0.021178 lr=0.343065 +[1,0]:INFO:root:Epoch[70] Batch[500] Loss[3.229] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[500] rmse=0.021205 lr=0.342933 +[1,0]:INFO:root:Epoch[70] Batch[600] Loss[2.935] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[600] rmse=0.021179 lr=0.342801 +[1,0]:INFO:root:Epoch[70] Batch[700] Loss[3.349] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[700] rmse=0.021188 lr=0.342668 +[1,0]:INFO:root:Epoch[70] Batch[800] Loss[3.097] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[800] rmse=0.021206 lr=0.342535 +[1,0]:INFO:root:Epoch[70] Batch[900] Loss[3.039] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[900] rmse=0.021219 lr=0.342402 +[1,0]:INFO:root:Epoch[70] Batch[1000] Loss[2.870] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[1000] rmse=0.021213 lr=0.342269 +[1,0]:INFO:root:Epoch[70] Batch[1100] Loss[3.391] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[1100] rmse=0.021221 lr=0.342136 +[1,0]:INFO:root:Epoch[70] Batch[1200] Loss[3.243] +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[1200] rmse=0.021224 lr=0.342003 +[1,0]:INFO:root:Epoch[70] Rank[0] Batch[1251] Time cost=400.80 Train-metric=0.021229 +[1,0]:INFO:root:Epoch[70] Speed: 3196.20 samples/sec +[1,0]:INFO:root:Epoch[71] Batch[100] Loss[2.844] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[100] rmse=0.021253 lr=0.341801 +[1,0]:INFO:root:Epoch[71] Batch[200] Loss[5.391] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[200] rmse=0.021241 lr=0.341668 +[1,0]:INFO:root:Epoch[71] Batch[300] Loss[3.576] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[300] rmse=0.021199 lr=0.341534 +[1,0]:INFO:root:Epoch[71] Batch[400] Loss[3.064] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[400] rmse=0.021229 lr=0.341400 +[1,0]:INFO:root:Epoch[71] Batch[500] Loss[4.663] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[500] rmse=0.021236 lr=0.341266 +[1,0]:INFO:root:Epoch[71] Batch[600] Loss[3.194] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[600] rmse=0.021245 lr=0.341132 +[1,0]:INFO:root:Epoch[71] Batch[700] Loss[2.812] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[700] rmse=0.021237 lr=0.340998 +[1,0]:INFO:root:Epoch[71] Batch[800] Loss[5.257] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[800] rmse=0.021252 lr=0.340863 +[1,0]:INFO:root:Epoch[71] Batch[900] Loss[2.988] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[900] rmse=0.021270 lr=0.340729 +[1,0]:INFO:root:Epoch[71] Batch[1000] Loss[3.046] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[1000] rmse=0.021283 lr=0.340594 +[1,0]:INFO:root:Epoch[71] Batch[1100] Loss[3.510] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[1100] rmse=0.021281 lr=0.340459 +[1,0]:INFO:root:Epoch[71] Batch[1200] Loss[2.969] +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[1200] rmse=0.021292 lr=0.340324 +[1,0]:INFO:root:Epoch[71] Rank[0] Batch[1251] Time cost=405.20 Train-metric=0.021295 +[1,0]:INFO:root:Epoch[71] Speed: 3161.46 samples/sec +[1,0]:INFO:root:Epoch[72] Batch[100] Loss[3.098] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[100] rmse=0.021329 lr=0.340121 +[1,0]:INFO:root:Epoch[72] Batch[200] Loss[2.871] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[200] rmse=0.021146 lr=0.339985 +[1,0]:INFO:root:Epoch[72] Batch[300] Loss[5.307] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[300] rmse=0.021173 lr=0.339850 +[1,0]:INFO:root:Epoch[72] Batch[400] Loss[2.870] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[400] rmse=0.021171 lr=0.339715 +[1,0]:INFO:root:Epoch[72] Batch[500] Loss[4.046] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[500] rmse=0.021166 lr=0.339579 +[1,0]:INFO:root:Epoch[72] Batch[600] Loss[3.337] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[600] rmse=0.021182 lr=0.339443 +[1,0]:INFO:root:Epoch[72] Batch[700] Loss[3.216] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[700] rmse=0.021196 lr=0.339307 +[1,0]:INFO:root:Epoch[72] Batch[800] Loss[3.160] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[800] rmse=0.021190 lr=0.339172 +[1,0]:INFO:root:Epoch[72] Batch[900] Loss[2.911] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[900] rmse=0.021172 lr=0.339035 +[1,0]:INFO:root:Epoch[72] Batch[1000] Loss[3.244] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[1000] rmse=0.021176 lr=0.338899 +[1,0]:INFO:root:Epoch[72] Batch[1100] Loss[3.153] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[1100] rmse=0.021182 lr=0.338763 +[1,0]:INFO:root:Epoch[72] Batch[1200] Loss[3.076] +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[1200] rmse=0.021200 lr=0.338627 +[1,0]:INFO:root:Epoch[72] Rank[0] Batch[1251] Time cost=400.68 Train-metric=0.021204 +[1,0]:INFO:root:Epoch[72] Speed: 3197.15 samples/sec +[1,0]:INFO:root:Epoch[73] Batch[100] Loss[3.026] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[100] rmse=0.021346 lr=0.338420 +[1,0]:INFO:root:Epoch[73] Batch[200] Loss[5.237] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[200] rmse=0.021390 lr=0.338283 +[1,0]:INFO:root:Epoch[73] Batch[300] Loss[4.965] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[300] rmse=0.021267 lr=0.338147 +[1,0]:INFO:root:Epoch[73] Batch[400] Loss[2.948] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[400] rmse=0.021285 lr=0.338010 +[1,0]:INFO:root:Epoch[73] Batch[500] Loss[3.165] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[500] rmse=0.021254 lr=0.337872 +[1,0]:INFO:root:Epoch[73] Batch[600] Loss[3.591] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[600] rmse=0.021269 lr=0.337735 +[1,0]:INFO:root:Epoch[73] Batch[700] Loss[5.228] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[700] rmse=0.021284 lr=0.337598 +[1,0]:INFO:root:Epoch[73] Batch[800] Loss[5.454] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[800] rmse=0.021309 lr=0.337460 +[1,0]:INFO:root:Epoch[73] Batch[900] Loss[4.237] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[900] rmse=0.021316 lr=0.337323 +[1,0]:INFO:root:Epoch[73] Batch[1000] Loss[2.674] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[1000] rmse=0.021301 lr=0.337185 +[1,0]:INFO:root:Epoch[73] Batch[1100] Loss[4.007] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[1100] rmse=0.021310 lr=0.337047 +[1,0]:INFO:root:Epoch[73] Batch[1200] Loss[2.827] +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[1200] rmse=0.021311 lr=0.336909 +[1,0]:INFO:root:Epoch[73] Rank[0] Batch[1251] Time cost=400.25 Train-metric=0.021305 +[1,0]:INFO:root:Epoch[73] Speed: 3200.54 samples/sec +[1,0]:INFO:root:Epoch[74] Batch[100] Loss[2.757] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[100] rmse=0.021104 lr=0.336701 +[1,0]:INFO:root:Epoch[74] Batch[200] Loss[4.952] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[200] rmse=0.021145 lr=0.336562 +[1,0]:INFO:root:Epoch[74] Batch[300] Loss[3.083] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[300] rmse=0.021183 lr=0.336424 +[1,0]:INFO:root:Epoch[74] Batch[400] Loss[2.756] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[400] rmse=0.021252 lr=0.336285 +[1,0]:INFO:root:Epoch[74] Batch[500] Loss[2.939] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[500] rmse=0.021242 lr=0.336147 +[1,0]:INFO:root:Epoch[74] Batch[600] Loss[3.494] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[600] rmse=0.021248 lr=0.336008 +[1,0]:INFO:root:Epoch[74] Batch[700] Loss[2.777] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[700] rmse=0.021216 lr=0.335869 +[1,0]:INFO:root:Epoch[74] Batch[800] Loss[4.254] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[800] rmse=0.021236 lr=0.335730 +[1,0]:INFO:root:Epoch[74] Batch[900] Loss[3.102] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[900] rmse=0.021231 lr=0.335591 +[1,0]:INFO:root:Epoch[74] Batch[1000] Loss[2.863] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[1000] rmse=0.021218 lr=0.335451 +[1,0]:INFO:root:Epoch[74] Batch[1100] Loss[3.175] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[1100] rmse=0.021231 lr=0.335312 +[1,0]:INFO:root:Epoch[74] Batch[1200] Loss[5.522] +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[1200] rmse=0.021241 lr=0.335173 +[1,0]:INFO:root:Epoch[74] Rank[0] Batch[1251] Time cost=399.05 Train-metric=0.021237 +[1,0]:INFO:root:Epoch[74] Speed: 3210.22 samples/sec +[1,0]:INFO:root:Epoch[74] Rank[0] Validation-accuracy=0.585600 Validation-top_k_accuracy_5=0.821700 +[1,0]:INFO:root:Epoch[75] Batch[100] Loss[2.875] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[100] rmse=0.021281 lr=0.334962 +[1,0]:INFO:root:Epoch[75] Batch[200] Loss[3.123] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[200] rmse=0.021141 lr=0.334822 +[1,0]:INFO:root:Epoch[75] Batch[300] Loss[2.793] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[300] rmse=0.021136 lr=0.334682 +[1,0]:INFO:root:Epoch[75] Batch[400] Loss[2.995] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[400] rmse=0.021057 lr=0.334542 +[1,0]:INFO:root:Epoch[75] Batch[500] Loss[3.086] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[500] rmse=0.021140 lr=0.334402 +[1,0]:INFO:root:Epoch[75] Batch[600] Loss[3.471] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[600] rmse=0.021142 lr=0.334261 +[1,0]:INFO:root:Epoch[75] Batch[700] Loss[3.012] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[700] rmse=0.021153 lr=0.334121 +[1,0]:INFO:root:Epoch[75] Batch[800] Loss[5.481] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[800] rmse=0.021148 lr=0.333980 +[1,0]:INFO:root:Epoch[75] Batch[900] Loss[3.524] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[900] rmse=0.021164 lr=0.333840 +[1,0]:INFO:root:Epoch[75] Batch[1000] Loss[3.039] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[1000] rmse=0.021184 lr=0.333699 +[1,0]:INFO:root:Epoch[75] Batch[1100] Loss[5.142] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[1100] rmse=0.021169 lr=0.333558 +[1,0]:INFO:root:Epoch[75] Batch[1200] Loss[3.558] +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[1200] rmse=0.021163 lr=0.333417 +[1,0]:INFO:root:Epoch[75] Rank[0] Batch[1251] Time cost=398.86 Train-metric=0.021176 +[1,0]:INFO:root:Epoch[75] Speed: 3211.74 samples/sec +[1,0]:INFO:root:Epoch[76] Batch[100] Loss[3.200] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[100] rmse=0.021257 lr=0.333204 +[1,0]:INFO:root:Epoch[76] Batch[200] Loss[3.357] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[200] rmse=0.021359 lr=0.333063 +[1,0]:INFO:root:Epoch[76] Batch[300] Loss[4.021] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[300] rmse=0.021267 lr=0.332921 +[1,0]:INFO:root:Epoch[76] Batch[400] Loss[2.919] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[400] rmse=0.021288 lr=0.332780 +[1,0]:INFO:root:Epoch[76] Batch[500] Loss[5.363] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[500] rmse=0.021243 lr=0.332638 +[1,0]:INFO:root:Epoch[76] Batch[600] Loss[5.322] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[600] rmse=0.021244 lr=0.332496 +[1,0]:INFO:root:Epoch[76] Batch[700] Loss[3.313] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[700] rmse=0.021243 lr=0.332354 +[1,0]:INFO:root:Epoch[76] Batch[800] Loss[5.376] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[800] rmse=0.021232 lr=0.332212 +[1,0]:INFO:root:Epoch[76] Batch[900] Loss[3.013] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[900] rmse=0.021232 lr=0.332070 +[1,0]:INFO:root:Epoch[76] Batch[1000] Loss[5.460] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[1000] rmse=0.021251 lr=0.331928 +[1,0]:INFO:root:Epoch[76] Batch[1100] Loss[5.197] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[1100] rmse=0.021244 lr=0.331785 +[1,0]:INFO:root:Epoch[76] Batch[1200] Loss[5.002] +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[1200] rmse=0.021256 lr=0.331643 +[1,0]:INFO:root:Epoch[76] Rank[0] Batch[1251] Time cost=398.67 Train-metric=0.021262 +[1,0]:INFO:root:Epoch[76] Speed: 3213.22 samples/sec +[1,0]:INFO:root:Epoch[77] Batch[100] Loss[2.908] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[100] rmse=0.021166 lr=0.331427 +[1,0]:INFO:root:Epoch[77] Batch[200] Loss[5.103] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[200] rmse=0.021201 lr=0.331285 +[1,0]:INFO:root:Epoch[77] Batch[300] Loss[3.030] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[300] rmse=0.021170 lr=0.331142 +[1,0]:INFO:root:Epoch[77] Batch[400] Loss[2.869] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[400] rmse=0.021171 lr=0.330999 +[1,0]:INFO:root:Epoch[77] Batch[500] Loss[2.973] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[500] rmse=0.021144 lr=0.330855 +[1,0]:INFO:root:Epoch[77] Batch[600] Loss[3.242] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[600] rmse=0.021138 lr=0.330712 +[1,0]:INFO:root:Epoch[77] Batch[700] Loss[5.130] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[700] rmse=0.021168 lr=0.330569 +[1,0]:INFO:root:Epoch[77] Batch[800] Loss[3.109] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[800] rmse=0.021173 lr=0.330425 +[1,0]:INFO:root:Epoch[77] Batch[900] Loss[4.981] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[900] rmse=0.021187 lr=0.330282 +[1,0]:INFO:root:Epoch[77] Batch[1000] Loss[5.067] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[1000] rmse=0.021217 lr=0.330138 +[1,0]:INFO:root:Epoch[77] Batch[1100] Loss[4.083] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[1100] rmse=0.021198 lr=0.329994 +[1,0]:INFO:root:Epoch[77] Batch[1200] Loss[3.672] +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[1200] rmse=0.021196 lr=0.329850 +[1,0]:INFO:root:Epoch[77] Rank[0] Batch[1251] Time cost=399.88 Train-metric=0.021192 +[1,0]:INFO:root:Epoch[77] Speed: 3203.48 samples/sec +[1,0]:INFO:root:Epoch[78] Batch[100] Loss[2.922] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[100] rmse=0.021180 lr=0.329632 +[1,0]:INFO:root:Epoch[78] Batch[200] Loss[2.858] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[200] rmse=0.021156 lr=0.329488 +[1,0]:INFO:root:Epoch[78] Batch[300] Loss[3.763] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[300] rmse=0.021203 lr=0.329344 +[1,0]:INFO:root:Epoch[78] Batch[400] Loss[2.992] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[400] rmse=0.021215 lr=0.329199 +[1,0]:INFO:root:Epoch[78] Batch[500] Loss[2.976] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[500] rmse=0.021255 lr=0.329055 +[1,0]:INFO:root:Epoch[78] Batch[600] Loss[3.264] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[600] rmse=0.021249 lr=0.328910 +[1,0]:INFO:root:Epoch[78] Batch[700] Loss[3.068] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[700] rmse=0.021248 lr=0.328765 +[1,0]:INFO:root:Epoch[78] Batch[800] Loss[2.909] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[800] rmse=0.021260 lr=0.328620 +[1,0]:INFO:root:Epoch[78] Batch[900] Loss[3.494] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[900] rmse=0.021247 lr=0.328475 +[1,0]:INFO:root:Epoch[78] Batch[1000] Loss[4.751] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[1000] rmse=0.021256 lr=0.328330 +[1,0]:INFO:root:Epoch[78] Batch[1100] Loss[2.974] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[1100] rmse=0.021255 lr=0.328184 +[1,0]:INFO:root:Epoch[78] Batch[1200] Loss[2.889] +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[1200] rmse=0.021259 lr=0.328039 +[1,0]:INFO:root:Epoch[78] Rank[0] Batch[1251] Time cost=399.02 Train-metric=0.021267 +[1,0]:INFO:root:Epoch[78] Speed: 3210.41 samples/sec +[1,0]:INFO:root:Epoch[79] Batch[100] Loss[2.936] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[100] rmse=0.021078 lr=0.327819 +[1,0]:INFO:root:Epoch[79] Batch[200] Loss[3.049] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[200] rmse=0.021160 lr=0.327674 +[1,0]:INFO:root:Epoch[79] Batch[300] Loss[3.479] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[300] rmse=0.021093 lr=0.327528 +[1,0]:INFO:root:Epoch[79] Batch[400] Loss[4.938] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[400] rmse=0.021120 lr=0.327382 +[1,0]:INFO:root:Epoch[79] Batch[500] Loss[3.743] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[500] rmse=0.021177 lr=0.327236 +[1,0]:INFO:root:Epoch[79] Batch[600] Loss[4.719] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[600] rmse=0.021139 lr=0.327090 +[1,0]:INFO:root:Epoch[79] Batch[700] Loss[3.353] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[700] rmse=0.021146 lr=0.326943 +[1,0]:INFO:root:Epoch[79] Batch[800] Loss[5.276] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[800] rmse=0.021179 lr=0.326797 +[1,0]:INFO:root:Epoch[79] Batch[900] Loss[3.222] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[900] rmse=0.021170 lr=0.326650 +[1,0]:INFO:root:Epoch[79] Batch[1000] Loss[3.096] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[1000] rmse=0.021182 lr=0.326504 +[1,0]:INFO:root:Epoch[79] Batch[1100] Loss[5.058] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[1100] rmse=0.021200 lr=0.326357 +[1,0]:INFO:root:Epoch[79] Batch[1200] Loss[3.500] +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[1200] rmse=0.021190 lr=0.326210 +[1,0]:INFO:root:Epoch[79] Rank[0] Batch[1251] Time cost=399.34 Train-metric=0.021195 +[1,0]:INFO:root:Epoch[79] Speed: 3207.89 samples/sec +[1,0]:INFO:root:Epoch[79] Rank[0] Validation-accuracy=0.598280 Validation-top_k_accuracy_5=0.833720 +[1,0]:INFO:root:Epoch[80] Batch[100] Loss[4.197] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[100] rmse=0.021067 lr=0.325988 +[1,0]:INFO:root:Epoch[80] Batch[200] Loss[3.863] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[200] rmse=0.021048 lr=0.325841 +[1,0]:INFO:root:Epoch[80] Batch[300] Loss[2.943] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[300] rmse=0.020991 lr=0.325694 +[1,0]:INFO:root:Epoch[80] Batch[400] Loss[2.894] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[400] rmse=0.021035 lr=0.325546 +[1,0]:INFO:root:Epoch[80] Batch[500] Loss[5.414] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[500] rmse=0.021080 lr=0.325399 +[1,0]:INFO:root:Epoch[80] Batch[600] Loss[2.842] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[600] rmse=0.021117 lr=0.325251 +[1,0]:INFO:root:Epoch[80] Batch[700] Loss[3.288] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[700] rmse=0.021099 lr=0.325104 +[1,0]:INFO:root:Epoch[80] Batch[800] Loss[2.980] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[800] rmse=0.021108 lr=0.324956 +[1,0]:INFO:root:Epoch[80] Batch[900] Loss[3.093] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[900] rmse=0.021132 lr=0.324808 +[1,0]:INFO:root:Epoch[80] Batch[1000] Loss[5.229] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[1000] rmse=0.021170 lr=0.324660 +[1,0]:INFO:root:Epoch[80] Batch[1100] Loss[2.964] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[1100] rmse=0.021163 lr=0.324512 +[1,0]:INFO:root:Epoch[80] Batch[1200] Loss[3.075] +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[1200] rmse=0.021178 lr=0.324363 +[1,0]:INFO:root:Epoch[80] Rank[0] Batch[1251] Time cost=398.42 Train-metric=0.021183 +[1,0]:INFO:root:Epoch[80] Speed: 3215.30 samples/sec +[1,0]:INFO:root:Epoch[81] Batch[100] Loss[2.797] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[100] rmse=0.021185 lr=0.324139 +[1,0]:INFO:root:Epoch[81] Batch[200] Loss[2.879] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[200] rmse=0.021193 lr=0.323991 +[1,0]:INFO:root:Epoch[81] Batch[300] Loss[5.346] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[300] rmse=0.021122 lr=0.323842 +[1,0]:INFO:root:Epoch[81] Batch[400] Loss[3.350] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[400] rmse=0.021106 lr=0.323693 +[1,0]:INFO:root:Epoch[81] Batch[500] Loss[3.180] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[500] rmse=0.021121 lr=0.323545 +[1,0]:INFO:root:Epoch[81] Batch[600] Loss[3.052] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[600] rmse=0.021110 lr=0.323396 +[1,0]:INFO:root:Epoch[81] Batch[700] Loss[4.462] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[700] rmse=0.021128 lr=0.323247 +[1,0]:INFO:root:Epoch[81] Batch[800] Loss[3.103] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[800] rmse=0.021142 lr=0.323097 +[1,0]:INFO:root:Epoch[81] Batch[900] Loss[4.484] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[900] rmse=0.021144 lr=0.322948 +[1,0]:INFO:root:Epoch[81] Batch[1000] Loss[3.138] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[1000] rmse=0.021140 lr=0.322799 +[1,0]:INFO:root:Epoch[81] Batch[1100] Loss[2.672] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[1100] rmse=0.021130 lr=0.322649 +[1,0]:INFO:root:Epoch[81] Batch[1200] Loss[5.064] +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[1200] rmse=0.021145 lr=0.322499 +[1,0]:INFO:root:Epoch[81] Rank[0] Batch[1251] Time cost=399.23 Train-metric=0.021153 +[1,0]:INFO:root:Epoch[81] Speed: 3208.72 samples/sec +[1,0]:INFO:root:Epoch[82] Batch[100] Loss[4.081] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[100] rmse=0.021187 lr=0.322273 +[1,0]:INFO:root:Epoch[82] Batch[200] Loss[3.920] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[200] rmse=0.021152 lr=0.322123 +[1,0]:INFO:root:Epoch[82] Batch[300] Loss[3.294] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[300] rmse=0.021132 lr=0.321973 +[1,0]:INFO:root:Epoch[82] Batch[400] Loss[3.689] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[400] rmse=0.021157 lr=0.321823 +[1,0]:INFO:root:Epoch[82] Batch[500] Loss[2.954] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[500] rmse=0.021180 lr=0.321673 +[1,0]:INFO:root:Epoch[82] Batch[600] Loss[5.294] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[600] rmse=0.021217 lr=0.321523 +[1,0]:INFO:root:Epoch[82] Batch[700] Loss[2.972] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[700] rmse=0.021237 lr=0.321372 +[1,0]:INFO:root:Epoch[82] Batch[800] Loss[2.834] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[800] rmse=0.021238 lr=0.321221 +[1,0]:INFO:root:Epoch[82] Batch[900] Loss[3.453] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[900] rmse=0.021245 lr=0.321071 +[1,0]:INFO:root:Epoch[82] Batch[1000] Loss[3.437] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[1000] rmse=0.021245 lr=0.320920 +[1,0]:INFO:root:Epoch[82] Batch[1100] Loss[3.439] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[1100] rmse=0.021233 lr=0.320769 +[1,0]:INFO:root:Epoch[82] Batch[1200] Loss[3.055] +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[1200] rmse=0.021236 lr=0.320618 +[1,0]:INFO:root:Epoch[82] Rank[0] Batch[1251] Time cost=399.47 Train-metric=0.021230 +[1,0]:INFO:root:Epoch[82] Speed: 3206.77 samples/sec +[1,0]:INFO:root:Epoch[83] Batch[100] Loss[2.815] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[100] rmse=0.021168 lr=0.320390 +[1,0]:INFO:root:Epoch[83] Batch[200] Loss[3.359] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[200] rmse=0.021143 lr=0.320239 +[1,0]:INFO:root:Epoch[83] Batch[300] Loss[3.578] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[300] rmse=0.021122 lr=0.320087 +[1,0]:INFO:root:Epoch[83] Batch[400] Loss[2.720] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[400] rmse=0.021152 lr=0.319936 +[1,0]:INFO:root:Epoch[83] Batch[500] Loss[2.616] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[500] rmse=0.021107 lr=0.319784 +[1,0]:INFO:root:Epoch[83] Batch[600] Loss[4.774] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[600] rmse=0.021123 lr=0.319632 +[1,0]:INFO:root:Epoch[83] Batch[700] Loss[4.192] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[700] rmse=0.021113 lr=0.319481 +[1,0]:INFO:root:Epoch[83] Batch[800] Loss[2.774] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[800] rmse=0.021117 lr=0.319329 +[1,0]:INFO:root:Epoch[83] Batch[900] Loss[2.820] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[900] rmse=0.021137 lr=0.319177 +[1,0]:INFO:root:Epoch[83] Batch[1000] Loss[3.955] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[1000] rmse=0.021143 lr=0.319025 +[1,0]:INFO:root:Epoch[83] Batch[1100] Loss[2.662] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[1100] rmse=0.021131 lr=0.318872 +[1,0]:INFO:root:Epoch[83] Batch[1200] Loss[3.917] +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[1200] rmse=0.021122 lr=0.318720 +[1,0]:INFO:root:Epoch[83] Rank[0] Batch[1251] Time cost=398.98 Train-metric=0.021127 +[1,0]:INFO:root:Epoch[83] Speed: 3210.76 samples/sec +[1,0]:INFO:root:Epoch[84] Batch[100] Loss[3.633] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[100] rmse=0.021126 lr=0.318490 +[1,0]:INFO:root:Epoch[84] Batch[200] Loss[3.567] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[200] rmse=0.021088 lr=0.318337 +[1,0]:INFO:root:Epoch[84] Batch[300] Loss[2.859] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[300] rmse=0.021114 lr=0.318184 +[1,0]:INFO:root:Epoch[84] Batch[400] Loss[2.840] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[400] rmse=0.021110 lr=0.318031 +[1,0]:INFO:root:Epoch[84] Batch[500] Loss[2.905] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[500] rmse=0.021117 lr=0.317879 +[1,0]:INFO:root:Epoch[84] Batch[600] Loss[4.889] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[600] rmse=0.021101 lr=0.317726 +[1,0]:INFO:root:Epoch[84] Batch[700] Loss[3.141] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[700] rmse=0.021116 lr=0.317572 +[1,0]:INFO:root:Epoch[84] Batch[800] Loss[5.414] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[800] rmse=0.021109 lr=0.317419 +[1,0]:INFO:root:Epoch[84] Batch[900] Loss[2.854] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[900] rmse=0.021110 lr=0.317266 +[1,0]:INFO:root:Epoch[84] Batch[1000] Loss[3.486] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[1000] rmse=0.021119 lr=0.317112 +[1,0]:INFO:root:Epoch[84] Batch[1100] Loss[4.454] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[1100] rmse=0.021114 lr=0.316959 +[1,0]:INFO:root:Epoch[84] Batch[1200] Loss[3.208] +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[1200] rmse=0.021132 lr=0.316805 +[1,0]:INFO:root:Epoch[84] Rank[0] Batch[1251] Time cost=398.99 Train-metric=0.021144 +[1,0]:INFO:root:Epoch[84] Speed: 3210.63 samples/sec +[1,0]:INFO:root:Epoch[84] Rank[0] Validation-accuracy=0.599040 Validation-top_k_accuracy_5=0.832480 +[1,0]:INFO:root:Epoch[85] Batch[100] Loss[3.041] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[100] rmse=0.021189 lr=0.316573 +[1,0]:INFO:root:Epoch[85] Batch[200] Loss[2.737] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[200] rmse=0.021054 lr=0.316419 +[1,0]:INFO:root:Epoch[85] Batch[300] Loss[5.308] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[300] rmse=0.021059 lr=0.316265 +[1,0]:INFO:root:Epoch[85] Batch[400] Loss[3.082] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[400] rmse=0.021097 lr=0.316111 +[1,0]:INFO:root:Epoch[85] Batch[500] Loss[3.265] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[500] rmse=0.021089 lr=0.315956 +[1,0]:INFO:root:Epoch[85] Batch[600] Loss[4.776] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[600] rmse=0.021088 lr=0.315802 +[1,0]:INFO:root:Epoch[85] Batch[700] Loss[3.337] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[700] rmse=0.021093 lr=0.315648 +[1,0]:INFO:root:Epoch[85] Batch[800] Loss[4.677] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[800] rmse=0.021109 lr=0.315493 +[1,0]:INFO:root:Epoch[85] Batch[900] Loss[3.128] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[900] rmse=0.021064 lr=0.315338 +[1,0]:INFO:root:Epoch[85] Batch[1000] Loss[2.987] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[1000] rmse=0.021099 lr=0.315184 +[1,0]:INFO:root:Epoch[85] Batch[1100] Loss[3.727] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[1100] rmse=0.021108 lr=0.315029 +[1,0]:INFO:root:Epoch[85] Batch[1200] Loss[4.450] +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[1200] rmse=0.021108 lr=0.314874 +[1,0]:INFO:root:Epoch[85] Rank[0] Batch[1251] Time cost=399.15 Train-metric=0.021105 +[1,0]:INFO:root:Epoch[85] Speed: 3209.41 samples/sec +[1,0]:INFO:root:Epoch[86] Batch[100] Loss[3.561] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[100] rmse=0.021343 lr=0.314640 +[1,0]:INFO:root:Epoch[86] Batch[200] Loss[2.786] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[200] rmse=0.021185 lr=0.314484 +[1,0]:INFO:root:Epoch[86] Batch[300] Loss[2.870] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[300] rmse=0.021168 lr=0.314329 +[1,0]:INFO:root:Epoch[86] Batch[400] Loss[5.382] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[400] rmse=0.021106 lr=0.314174 +[1,0]:INFO:root:Epoch[86] Batch[500] Loss[2.655] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[500] rmse=0.021116 lr=0.314018 +[1,0]:INFO:root:Epoch[86] Batch[600] Loss[3.329] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[600] rmse=0.021153 lr=0.313862 +[1,0]:INFO:root:Epoch[86] Batch[700] Loss[2.816] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[700] rmse=0.021142 lr=0.313707 +[1,0]:INFO:root:Epoch[86] Batch[800] Loss[2.830] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[800] rmse=0.021108 lr=0.313551 +[1,0]:INFO:root:Epoch[86] Batch[900] Loss[3.127] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[900] rmse=0.021127 lr=0.313395 +[1,0]:INFO:root:Epoch[86] Batch[1000] Loss[4.704] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[1000] rmse=0.021137 lr=0.313239 +[1,0]:INFO:root:Epoch[86] Batch[1100] Loss[3.115] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[1100] rmse=0.021122 lr=0.313083 +[1,0]:INFO:root:Epoch[86] Batch[1200] Loss[2.784] +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[1200] rmse=0.021115 lr=0.312926 +[1,0]:INFO:root:Epoch[86] Rank[0] Batch[1251] Time cost=399.45 Train-metric=0.021104 +[1,0]:INFO:root:Epoch[86] Speed: 3206.97 samples/sec +[1,0]:INFO:root:Epoch[87] Batch[100] Loss[3.440] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[100] rmse=0.020928 lr=0.312690 +[1,0]:INFO:root:Epoch[87] Batch[200] Loss[3.104] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[200] rmse=0.020948 lr=0.312534 +[1,0]:INFO:root:Epoch[87] Batch[300] Loss[2.993] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[300] rmse=0.021046 lr=0.312377 +[1,0]:INFO:root:Epoch[87] Batch[400] Loss[3.035] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[400] rmse=0.021118 lr=0.312220 +[1,0]:INFO:root:Epoch[87] Batch[500] Loss[3.513] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[500] rmse=0.021149 lr=0.312064 +[1,0]:INFO:root:Epoch[87] Batch[600] Loss[2.867] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[600] rmse=0.021207 lr=0.311907 +[1,0]:INFO:root:Epoch[87] Batch[700] Loss[3.032] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[700] rmse=0.021212 lr=0.311750 +[1,0]:INFO:root:Epoch[87] Batch[800] Loss[2.909] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[800] rmse=0.021186 lr=0.311593 +[1,0]:INFO:root:Epoch[87] Batch[900] Loss[5.385] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[900] rmse=0.021146 lr=0.311435 +[1,0]:INFO:root:Epoch[87] Batch[1000] Loss[4.886] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[1000] rmse=0.021137 lr=0.311278 +[1,0]:INFO:root:Epoch[87] Batch[1100] Loss[4.888] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[1100] rmse=0.021135 lr=0.311121 +[1,0]:INFO:root:Epoch[87] Batch[1200] Loss[3.017] +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[1200] rmse=0.021142 lr=0.310963 +[1,0]:INFO:root:Epoch[87] Rank[0] Batch[1251] Time cost=399.40 Train-metric=0.021155 +[1,0]:INFO:root:Epoch[87] Speed: 3207.39 samples/sec +[1,0]:INFO:root:Epoch[88] Batch[100] Loss[3.124] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[100] rmse=0.021127 lr=0.310725 +[1,0]:INFO:root:Epoch[88] Batch[200] Loss[3.254] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[200] rmse=0.021205 lr=0.310567 +[1,0]:INFO:root:Epoch[88] Batch[300] Loss[5.539] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[300] rmse=0.021169 lr=0.310410 +[1,0]:INFO:root:Epoch[88] Batch[400] Loss[3.037] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[400] rmse=0.021135 lr=0.310252 +[1,0]:INFO:root:Epoch[88] Batch[500] Loss[3.252] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[500] rmse=0.021118 lr=0.310094 +[1,0]:INFO:root:Epoch[88] Batch[600] Loss[3.407] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[600] rmse=0.021088 lr=0.309935 +[1,0]:INFO:root:Epoch[88] Batch[700] Loss[4.120] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[700] rmse=0.021089 lr=0.309777 +[1,0]:INFO:root:Epoch[88] Batch[800] Loss[5.405] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[800] rmse=0.021091 lr=0.309619 +[1,0]:INFO:root:Epoch[88] Batch[900] Loss[2.732] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[900] rmse=0.021085 lr=0.309460 +[1,0]:INFO:root:Epoch[88] Batch[1000] Loss[3.361] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[1000] rmse=0.021095 lr=0.309302 +[1,0]:INFO:root:Epoch[88] Batch[1100] Loss[3.453] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[1100] rmse=0.021096 lr=0.309143 +[1,0]:INFO:root:Epoch[88] Batch[1200] Loss[2.680] +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[1200] rmse=0.021111 lr=0.308984 +[1,0]:INFO:root:Epoch[88] Rank[0] Batch[1251] Time cost=399.46 Train-metric=0.021113 +[1,0]:INFO:root:Epoch[88] Speed: 3206.92 samples/sec +[1,0]:INFO:root:Epoch[89] Batch[100] Loss[5.354] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[100] rmse=0.021053 lr=0.308745 +[1,0]:INFO:root:Epoch[89] Batch[200] Loss[2.837] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[200] rmse=0.021075 lr=0.308586 +[1,0]:INFO:root:Epoch[89] Batch[300] Loss[2.869] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[300] rmse=0.021129 lr=0.308426 +[1,0]:INFO:root:Epoch[89] Batch[400] Loss[3.302] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[400] rmse=0.021091 lr=0.308267 +[1,0]:INFO:root:Epoch[89] Batch[500] Loss[3.008] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[500] rmse=0.021068 lr=0.308108 +[1,0]:INFO:root:Epoch[89] Batch[600] Loss[4.943] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[600] rmse=0.021073 lr=0.307949 +[1,0]:INFO:root:Epoch[89] Batch[700] Loss[4.848] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[700] rmse=0.021105 lr=0.307789 +[1,0]:INFO:root:Epoch[89] Batch[800] Loss[3.206] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[800] rmse=0.021089 lr=0.307630 +[1,0]:INFO:root:Epoch[89] Batch[900] Loss[3.593] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[900] rmse=0.021099 lr=0.307470 +[1,0]:INFO:root:Epoch[89] Batch[1000] Loss[3.011] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[1000] rmse=0.021102 lr=0.307310 +[1,0]:INFO:root:Epoch[89] Batch[1100] Loss[2.955] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[1100] rmse=0.021106 lr=0.307150 +[1,0]:INFO:root:Epoch[89] Batch[1200] Loss[3.199] +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[1200] rmse=0.021128 lr=0.306990 +[1,0]:INFO:root:Epoch[89] Rank[0] Batch[1251] Time cost=399.32 Train-metric=0.021124 +[1,0]:INFO:root:Epoch[89] Speed: 3208.03 samples/sec +[1,0]:INFO:root:Epoch[89] Rank[0] Validation-accuracy=0.588660 Validation-top_k_accuracy_5=0.822760 +[1,0]:INFO:root:Epoch[90] Batch[100] Loss[3.013] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[100] rmse=0.020665 lr=0.306749 +[1,0]:INFO:root:Epoch[90] Batch[200] Loss[3.856] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[200] rmse=0.020732 lr=0.306588 +[1,0]:INFO:root:Epoch[90] Batch[300] Loss[4.015] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[300] rmse=0.020917 lr=0.306428 +[1,0]:INFO:root:Epoch[90] Batch[400] Loss[4.100] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[400] rmse=0.020943 lr=0.306268 +[1,0]:INFO:root:Epoch[90] Batch[500] Loss[2.759] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[500] rmse=0.021011 lr=0.306107 +[1,0]:INFO:root:Epoch[90] Batch[600] Loss[5.037] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[600] rmse=0.021022 lr=0.305947 +[1,0]:INFO:root:Epoch[90] Batch[700] Loss[3.168] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[700] rmse=0.021026 lr=0.305786 +[1,0]:INFO:root:Epoch[90] Batch[800] Loss[2.803] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[800] rmse=0.021058 lr=0.305625 +[1,0]:INFO:root:Epoch[90] Batch[900] Loss[5.361] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[900] rmse=0.021074 lr=0.305464 +[1,0]:INFO:root:Epoch[90] Batch[1000] Loss[2.880] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[1000] rmse=0.021083 lr=0.305303 +[1,0]:INFO:root:Epoch[90] Batch[1100] Loss[4.901] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[1100] rmse=0.021079 lr=0.305142 +[1,0]:INFO:root:Epoch[90] Batch[1200] Loss[5.329] +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[1200] rmse=0.021100 lr=0.304981 +[1,0]:INFO:root:Epoch[90] Rank[0] Batch[1251] Time cost=398.93 Train-metric=0.021105 +[1,0]:INFO:root:Epoch[90] Speed: 3211.12 samples/sec +[1,0]:INFO:root:Epoch[91] Batch[100] Loss[2.812] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[100] rmse=0.021068 lr=0.304738 +[1,0]:INFO:root:Epoch[91] Batch[200] Loss[5.519] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[200] rmse=0.020965 lr=0.304576 +[1,0]:INFO:root:Epoch[91] Batch[300] Loss[3.159] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[300] rmse=0.021001 lr=0.304415 +[1,0]:INFO:root:Epoch[91] Batch[400] Loss[3.083] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[400] rmse=0.020997 lr=0.304253 +[1,0]:INFO:root:Epoch[91] Batch[500] Loss[3.119] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[500] rmse=0.021041 lr=0.304092 +[1,0]:INFO:root:Epoch[91] Batch[600] Loss[3.022] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[600] rmse=0.021061 lr=0.303930 +[1,0]:INFO:root:Epoch[91] Batch[700] Loss[2.874] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[700] rmse=0.021086 lr=0.303768 +[1,0]:INFO:root:Epoch[91] Batch[800] Loss[4.648] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[800] rmse=0.021103 lr=0.303606 +[1,0]:INFO:root:Epoch[91] Batch[900] Loss[3.020] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[900] rmse=0.021104 lr=0.303444 +[1,0]:INFO:root:Epoch[91] Batch[1000] Loss[5.217] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[1000] rmse=0.021101 lr=0.303282 +[1,0]:INFO:root:Epoch[91] Batch[1100] Loss[4.042] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[1100] rmse=0.021112 lr=0.303120 +[1,0]:INFO:root:Epoch[91] Batch[1200] Loss[2.755] +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[1200] rmse=0.021115 lr=0.302957 +[1,0]:INFO:root:Epoch[91] Rank[0] Batch[1251] Time cost=399.44 Train-metric=0.021116 +[1,0]:INFO:root:Epoch[91] Speed: 3207.06 samples/sec +[1,0]:INFO:root:Epoch[92] Batch[100] Loss[4.780] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[100] rmse=0.020955 lr=0.302712 +[1,0]:INFO:root:Epoch[92] Batch[200] Loss[5.159] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[200] rmse=0.021030 lr=0.302550 +[1,0]:INFO:root:Epoch[92] Batch[300] Loss[2.868] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[300] rmse=0.021046 lr=0.302387 +[1,0]:INFO:root:Epoch[92] Batch[400] Loss[2.700] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[400] rmse=0.021053 lr=0.302224 +[1,0]:INFO:root:Epoch[92] Batch[500] Loss[3.045] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[500] rmse=0.021066 lr=0.302061 +[1,0]:INFO:root:Epoch[92] Batch[600] Loss[4.004] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[600] rmse=0.021088 lr=0.301899 +[1,0]:INFO:root:Epoch[92] Batch[700] Loss[5.272] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[700] rmse=0.021082 lr=0.301736 +[1,0]:INFO:root:Epoch[92] Batch[800] Loss[5.314] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[800] rmse=0.021088 lr=0.301572 +[1,0]:INFO:root:Epoch[92] Batch[900] Loss[3.158] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[900] rmse=0.021107 lr=0.301409 +[1,0]:INFO:root:Epoch[92] Batch[1000] Loss[3.115] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[1000] rmse=0.021106 lr=0.301246 +[1,0]:INFO:root:Epoch[92] Batch[1100] Loss[5.352] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[1100] rmse=0.021111 lr=0.301083 +[1,0]:INFO:root:Epoch[92] Batch[1200] Loss[2.966] +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[1200] rmse=0.021107 lr=0.300919 +[1,0]:INFO:root:Epoch[92] Rank[0] Batch[1251] Time cost=398.48 Train-metric=0.021107 +[1,0]:INFO:root:Epoch[92] Speed: 3214.81 samples/sec +[1,0]:INFO:root:Epoch[93] Batch[100] Loss[4.892] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[100] rmse=0.020893 lr=0.300672 +[1,0]:INFO:root:Epoch[93] Batch[200] Loss[2.842] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[200] rmse=0.020826 lr=0.300509 +[1,0]:INFO:root:Epoch[93] Batch[300] Loss[3.177] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[300] rmse=0.020920 lr=0.300345 +[1,0]:INFO:root:Epoch[93] Batch[400] Loss[3.029] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[400] rmse=0.020930 lr=0.300181 +[1,0]:INFO:root:Epoch[93] Batch[500] Loss[2.920] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[500] rmse=0.020927 lr=0.300017 +[1,0]:INFO:root:Epoch[93] Batch[600] Loss[3.756] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[600] rmse=0.020962 lr=0.299853 +[1,0]:INFO:root:Epoch[93] Batch[700] Loss[3.454] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[700] rmse=0.020983 lr=0.299689 +[1,0]:INFO:root:Epoch[93] Batch[800] Loss[2.715] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[800] rmse=0.021001 lr=0.299525 +[1,0]:INFO:root:Epoch[93] Batch[900] Loss[3.110] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[900] rmse=0.021040 lr=0.299360 +[1,0]:INFO:root:Epoch[93] Batch[1000] Loss[3.830] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[1000] rmse=0.021056 lr=0.299196 +[1,0]:INFO:root:Epoch[93] Batch[1100] Loss[3.052] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[1100] rmse=0.021071 lr=0.299031 +[1,0]:INFO:root:Epoch[93] Batch[1200] Loss[4.080] +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[1200] rmse=0.021080 lr=0.298867 +[1,0]:INFO:root:Epoch[93] Rank[0] Batch[1251] Time cost=399.19 Train-metric=0.021077 +[1,0]:INFO:root:Epoch[93] Speed: 3209.09 samples/sec +[1,0]:INFO:root:Epoch[94] Batch[100] Loss[3.244] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[100] rmse=0.021015 lr=0.298618 +[1,0]:INFO:root:Epoch[94] Batch[200] Loss[3.181] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[200] rmse=0.020889 lr=0.298453 +[1,0]:INFO:root:Epoch[94] Batch[300] Loss[2.910] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[300] rmse=0.021017 lr=0.298288 +[1,0]:INFO:root:Epoch[94] Batch[400] Loss[2.681] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[400] rmse=0.021002 lr=0.298123 +[1,0]:INFO:root:Epoch[94] Batch[500] Loss[2.796] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[500] rmse=0.021075 lr=0.297958 +[1,0]:INFO:root:Epoch[94] Batch[600] Loss[3.095] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[600] rmse=0.021061 lr=0.297793 +[1,0]:INFO:root:Epoch[94] Batch[700] Loss[3.247] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[700] rmse=0.021052 lr=0.297628 +[1,0]:INFO:root:Epoch[94] Batch[800] Loss[2.811] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[800] rmse=0.021055 lr=0.297463 +[1,0]:INFO:root:Epoch[94] Batch[900] Loss[2.657] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[900] rmse=0.021072 lr=0.297297 +[1,0]:INFO:root:Epoch[94] Batch[1000] Loss[3.087] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[1000] rmse=0.021072 lr=0.297132 +[1,0]:INFO:root:Epoch[94] Batch[1100] Loss[2.945] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[1100] rmse=0.021064 lr=0.296966 +[1,0]:INFO:root:Epoch[94] Batch[1200] Loss[2.811] +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[1200] rmse=0.021061 lr=0.296800 +[1,0]:INFO:root:Epoch[94] Rank[0] Batch[1251] Time cost=400.41 Train-metric=0.021064 +[1,0]:INFO:root:Epoch[94] Speed: 3199.28 samples/sec +[1,0]:INFO:root:Epoch[94] Rank[0] Validation-accuracy=0.604720 Validation-top_k_accuracy_5=0.834480 +[1,0]:INFO:root:Epoch[95] Batch[100] Loss[2.679] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[100] rmse=0.020916 lr=0.296550 +[1,0]:INFO:root:Epoch[95] Batch[200] Loss[2.686] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[200] rmse=0.020914 lr=0.296384 +[1,0]:INFO:root:Epoch[95] Batch[300] Loss[3.007] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[300] rmse=0.020937 lr=0.296218 +[1,0]:INFO:root:Epoch[95] Batch[400] Loss[3.187] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[400] rmse=0.020978 lr=0.296052 +[1,0]:INFO:root:Epoch[95] Batch[500] Loss[5.196] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[500] rmse=0.021044 lr=0.295886 +[1,0]:INFO:root:Epoch[95] Batch[600] Loss[3.143] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[600] rmse=0.021035 lr=0.295720 +[1,0]:INFO:root:Epoch[95] Batch[700] Loss[4.565] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[700] rmse=0.021003 lr=0.295553 +[1,0]:INFO:root:Epoch[95] Batch[800] Loss[4.031] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[800] rmse=0.021002 lr=0.295387 +[1,0]:INFO:root:Epoch[95] Batch[900] Loss[4.993] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[900] rmse=0.020987 lr=0.295221 +[1,0]:INFO:root:Epoch[95] Batch[1000] Loss[4.458] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[1000] rmse=0.020991 lr=0.295054 +[1,0]:INFO:root:Epoch[95] Batch[1100] Loss[3.731] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[1100] rmse=0.021022 lr=0.294887 +[1,0]:INFO:root:Epoch[95] Batch[1200] Loss[2.723] +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[1200] rmse=0.021026 lr=0.294721 +[1,0]:INFO:root:Epoch[95] Rank[0] Batch[1251] Time cost=402.17 Train-metric=0.021035 +[1,0]:INFO:root:Epoch[95] Speed: 3185.28 samples/sec +[1,0]:INFO:root:Epoch[96] Batch[100] Loss[3.084] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[100] rmse=0.021150 lr=0.294469 +[1,0]:INFO:root:Epoch[96] Batch[200] Loss[2.669] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[200] rmse=0.021011 lr=0.294302 +[1,0]:INFO:root:Epoch[96] Batch[300] Loss[3.207] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[300] rmse=0.021060 lr=0.294135 +[1,0]:INFO:root:Epoch[96] Batch[400] Loss[2.556] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[400] rmse=0.021059 lr=0.293968 +[1,0]:INFO:root:Epoch[96] Batch[500] Loss[3.080] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[500] rmse=0.021052 lr=0.293800 +[1,0]:INFO:root:Epoch[96] Batch[600] Loss[2.804] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[600] rmse=0.021035 lr=0.293633 +[1,0]:INFO:root:Epoch[96] Batch[700] Loss[2.929] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[700] rmse=0.021046 lr=0.293466 +[1,0]:INFO:root:Epoch[96] Batch[800] Loss[3.270] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[800] rmse=0.021050 lr=0.293298 +[1,0]:INFO:root:Epoch[96] Batch[900] Loss[5.085] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[900] rmse=0.021050 lr=0.293131 +[1,0]:INFO:root:Epoch[96] Batch[1000] Loss[4.671] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[1000] rmse=0.021051 lr=0.292963 +[1,0]:INFO:root:Epoch[96] Batch[1100] Loss[2.905] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[1100] rmse=0.021056 lr=0.292795 +[1,0]:INFO:root:Epoch[96] Batch[1200] Loss[2.945] +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[1200] rmse=0.021064 lr=0.292627 +[1,0]:INFO:root:Epoch[96] Rank[0] Batch[1251] Time cost=403.18 Train-metric=0.021070 +[1,0]:INFO:root:Epoch[96] Speed: 3177.31 samples/sec +[1,0]:INFO:root:Epoch[97] Batch[100] Loss[4.244] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[100] rmse=0.020851 lr=0.292374 +[1,0]:INFO:root:Epoch[97] Batch[200] Loss[2.789] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[200] rmse=0.020953 lr=0.292206 +[1,0]:INFO:root:Epoch[97] Batch[300] Loss[4.082] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[300] rmse=0.020928 lr=0.292038 +[1,0]:INFO:root:Epoch[97] Batch[400] Loss[3.284] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[400] rmse=0.020955 lr=0.291870 +[1,0]:INFO:root:Epoch[97] Batch[500] Loss[4.269] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[500] rmse=0.020956 lr=0.291701 +[1,0]:INFO:root:Epoch[97] Batch[600] Loss[4.670] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[600] rmse=0.020965 lr=0.291533 +[1,0]:INFO:root:Epoch[97] Batch[700] Loss[4.368] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[700] rmse=0.021020 lr=0.291365 +[1,0]:INFO:root:Epoch[97] Batch[800] Loss[2.771] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[800] rmse=0.021025 lr=0.291196 +[1,0]:INFO:root:Epoch[97] Batch[900] Loss[2.747] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[900] rmse=0.021022 lr=0.291028 +[1,0]:INFO:root:Epoch[97] Batch[1000] Loss[4.692] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[1000] rmse=0.021026 lr=0.290859 +[1,0]:INFO:root:Epoch[97] Batch[1100] Loss[3.475] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[1100] rmse=0.021029 lr=0.290690 +[1,0]:INFO:root:Epoch[97] Batch[1200] Loss[2.836] +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[1200] rmse=0.021025 lr=0.290521 +[1,0]:INFO:root:Epoch[97] Rank[0] Batch[1251] Time cost=399.52 Train-metric=0.021020 +[1,0]:INFO:root:Epoch[97] Speed: 3206.39 samples/sec +[1,0]:INFO:root:Epoch[98] Batch[100] Loss[4.449] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[100] rmse=0.020840 lr=0.290266 +[1,0]:INFO:root:Epoch[98] Batch[200] Loss[3.144] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[200] rmse=0.020870 lr=0.290097 +[1,0]:INFO:root:Epoch[98] Batch[300] Loss[4.637] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[300] rmse=0.020904 lr=0.289928 +[1,0]:INFO:root:Epoch[98] Batch[400] Loss[2.930] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[400] rmse=0.020956 lr=0.289759 +[1,0]:INFO:root:Epoch[98] Batch[500] Loss[3.002] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[500] rmse=0.020987 lr=0.289590 +[1,0]:INFO:root:Epoch[98] Batch[600] Loss[4.981] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[600] rmse=0.020920 lr=0.289420 +[1,0]:INFO:root:Epoch[98] Batch[700] Loss[2.995] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[700] rmse=0.020944 lr=0.289251 +[1,0]:INFO:root:Epoch[98] Batch[800] Loss[2.990] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[800] rmse=0.020951 lr=0.289081 +[1,0]:INFO:root:Epoch[98] Batch[900] Loss[3.081] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[900] rmse=0.020945 lr=0.288912 +[1,0]:INFO:root:Epoch[98] Batch[1000] Loss[3.144] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[1000] rmse=0.020959 lr=0.288742 +[1,0]:INFO:root:Epoch[98] Batch[1100] Loss[4.498] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[1100] rmse=0.020943 lr=0.288572 +[1,0]:INFO:root:Epoch[98] Batch[1200] Loss[3.273] +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[1200] rmse=0.020949 lr=0.288402 +[1,0]:INFO:root:Epoch[98] Rank[0] Batch[1251] Time cost=399.16 Train-metric=0.020960 +[1,0]:INFO:root:Epoch[98] Speed: 3209.32 samples/sec +[1,0]:INFO:root:Epoch[99] Batch[100] Loss[3.178] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[100] rmse=0.021020 lr=0.288146 +[1,0]:INFO:root:Epoch[99] Batch[200] Loss[3.648] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[200] rmse=0.020929 lr=0.287976 +[1,0]:INFO:root:Epoch[99] Batch[300] Loss[3.922] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[300] rmse=0.020977 lr=0.287806 +[1,0]:INFO:root:Epoch[99] Batch[400] Loss[3.536] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[400] rmse=0.020973 lr=0.287635 +[1,0]:INFO:root:Epoch[99] Batch[500] Loss[3.056] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[500] rmse=0.020948 lr=0.287465 +[1,0]:INFO:root:Epoch[99] Batch[600] Loss[3.231] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[600] rmse=0.020975 lr=0.287295 +[1,0]:INFO:root:Epoch[99] Batch[700] Loss[3.732] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[700] rmse=0.021010 lr=0.287124 +[1,0]:INFO:root:Epoch[99] Batch[800] Loss[3.444] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[800] rmse=0.021002 lr=0.286954 +[1,0]:INFO:root:Epoch[99] Batch[900] Loss[2.791] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[900] rmse=0.020971 lr=0.286783 +[1,0]:INFO:root:Epoch[99] Batch[1000] Loss[2.778] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[1000] rmse=0.020957 lr=0.286613 +[1,0]:INFO:root:Epoch[99] Batch[1100] Loss[2.823] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[1100] rmse=0.020964 lr=0.286442 +[1,0]:INFO:root:Epoch[99] Batch[1200] Loss[2.649] +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[1200] rmse=0.020971 lr=0.286271 +[1,0]:INFO:root:Epoch[99] Rank[0] Batch[1251] Time cost=399.53 Train-metric=0.020990 +[1,0]:INFO:root:Epoch[99] Speed: 3206.36 samples/sec +[1,0]:INFO:root:Epoch[99] Rank[0] Validation-accuracy=0.596420 Validation-top_k_accuracy_5=0.831900 +[1,0]:INFO:root:Epoch[100] Batch[100] Loss[2.886] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[100] rmse=0.020695 lr=0.286013 +[1,0]:INFO:root:Epoch[100] Batch[200] Loss[5.084] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[200] rmse=0.020820 lr=0.285842 +[1,0]:INFO:root:Epoch[100] Batch[300] Loss[2.883] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[300] rmse=0.020855 lr=0.285671 +[1,0]:INFO:root:Epoch[100] Batch[400] Loss[4.013] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[400] rmse=0.020888 lr=0.285500 +[1,0]:INFO:root:Epoch[100] Batch[500] Loss[3.710] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[500] rmse=0.020904 lr=0.285329 +[1,0]:INFO:root:Epoch[100] Batch[600] Loss[5.536] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[600] rmse=0.020917 lr=0.285157 +[1,0]:INFO:root:Epoch[100] Batch[700] Loss[2.918] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[700] rmse=0.020951 lr=0.284986 +[1,0]:INFO:root:Epoch[100] Batch[800] Loss[2.845] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[800] rmse=0.020945 lr=0.284814 +[1,0]:INFO:root:Epoch[100] Batch[900] Loss[2.910] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[900] rmse=0.020947 lr=0.284643 +[1,0]:INFO:root:Epoch[100] Batch[1000] Loss[3.176] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[1000] rmse=0.020962 lr=0.284471 +[1,0]:INFO:root:Epoch[100] Batch[1100] Loss[3.299] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[1100] rmse=0.020975 lr=0.284300 +[1,0]:INFO:root:Epoch[100] Batch[1200] Loss[4.983] +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[1200] rmse=0.020991 lr=0.284128 +[1,0]:INFO:root:Epoch[100] Rank[0] Batch[1251] Time cost=398.57 Train-metric=0.021000 +[1,0]:INFO:root:Epoch[100] Speed: 3214.05 samples/sec +[1,0]:INFO:root:Epoch[101] Batch[100] Loss[2.880] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[100] rmse=0.021006 lr=0.283868 +[1,0]:INFO:root:Epoch[101] Batch[200] Loss[4.172] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[200] rmse=0.020976 lr=0.283696 +[1,0]:INFO:root:Epoch[101] Batch[300] Loss[3.504] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[300] rmse=0.020961 lr=0.283524 +[1,0]:INFO:root:Epoch[101] Batch[400] Loss[3.017] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[400] rmse=0.020953 lr=0.283352 +[1,0]:INFO:root:Epoch[101] Batch[500] Loss[2.911] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[500] rmse=0.020976 lr=0.283180 +[1,0]:INFO:root:Epoch[101] Batch[600] Loss[2.971] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[600] rmse=0.020963 lr=0.283008 +[1,0]:INFO:root:Epoch[101] Batch[700] Loss[2.657] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[700] rmse=0.020997 lr=0.282835 +[1,0]:INFO:root:Epoch[101] Batch[800] Loss[3.145] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[800] rmse=0.020976 lr=0.282663 +[1,0]:INFO:root:Epoch[101] Batch[900] Loss[5.344] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[900] rmse=0.020969 lr=0.282490 +[1,0]:INFO:root:Epoch[101] Batch[1000] Loss[3.438] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[1000] rmse=0.020994 lr=0.282318 +[1,0]:INFO:root:Epoch[101] Batch[1100] Loss[3.078] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[1100] rmse=0.021004 lr=0.282145 +[1,0]:INFO:root:Epoch[101] Batch[1200] Loss[2.899] +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[1200] rmse=0.020997 lr=0.281973 +[1,0]:INFO:root:Epoch[101] Rank[0] Batch[1251] Time cost=399.42 Train-metric=0.021008 +[1,0]:INFO:root:Epoch[101] Speed: 3207.21 samples/sec +[1,0]:INFO:root:Epoch[102] Batch[100] Loss[2.841] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[100] rmse=0.020832 lr=0.281712 +[1,0]:INFO:root:Epoch[102] Batch[200] Loss[2.723] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[200] rmse=0.020812 lr=0.281539 +[1,0]:INFO:root:Epoch[102] Batch[300] Loss[2.819] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[300] rmse=0.020830 lr=0.281366 +[1,0]:INFO:root:Epoch[102] Batch[400] Loss[3.402] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[400] rmse=0.020814 lr=0.281193 +[1,0]:INFO:root:Epoch[102] Batch[500] Loss[5.270] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[500] rmse=0.020861 lr=0.281020 +[1,0]:INFO:root:Epoch[102] Batch[600] Loss[5.123] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[600] rmse=0.020886 lr=0.280846 +[1,0]:INFO:root:Epoch[102] Batch[700] Loss[3.029] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[700] rmse=0.020922 lr=0.280673 +[1,0]:INFO:root:Epoch[102] Batch[800] Loss[5.052] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[800] rmse=0.020913 lr=0.280500 +[1,0]:INFO:root:Epoch[102] Batch[900] Loss[3.040] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[900] rmse=0.020919 lr=0.280326 +[1,0]:INFO:root:Epoch[102] Batch[1000] Loss[4.214] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[1000] rmse=0.020926 lr=0.280153 +[1,0]:INFO:root:Epoch[102] Batch[1100] Loss[3.164] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[1100] rmse=0.020925 lr=0.279979 +[1,0]:INFO:root:Epoch[102] Batch[1200] Loss[3.626] +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[1200] rmse=0.020941 lr=0.279806 +[1,0]:INFO:root:Epoch[102] Rank[0] Batch[1251] Time cost=399.27 Train-metric=0.020940 +[1,0]:INFO:root:Epoch[102] Speed: 3208.41 samples/sec +[1,0]:INFO:root:Epoch[103] Batch[100] Loss[3.356] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[100] rmse=0.020750 lr=0.279544 +[1,0]:INFO:root:Epoch[103] Batch[200] Loss[3.771] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[200] rmse=0.020871 lr=0.279370 +[1,0]:INFO:root:Epoch[103] Batch[300] Loss[5.503] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[300] rmse=0.020862 lr=0.279196 +[1,0]:INFO:root:Epoch[103] Batch[400] Loss[2.885] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[400] rmse=0.020905 lr=0.279022 +[1,0]:INFO:root:Epoch[103] Batch[500] Loss[3.020] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[500] rmse=0.020967 lr=0.278848 +[1,0]:INFO:root:Epoch[103] Batch[600] Loss[2.981] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[600] rmse=0.020948 lr=0.278674 +[1,0]:INFO:root:Epoch[103] Batch[700] Loss[4.708] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[700] rmse=0.020955 lr=0.278500 +[1,0]:INFO:root:Epoch[103] Batch[800] Loss[3.072] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[800] rmse=0.020963 lr=0.278326 +[1,0]:INFO:root:Epoch[103] Batch[900] Loss[2.666] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[900] rmse=0.020981 lr=0.278151 +[1,0]:INFO:root:Epoch[103] Batch[1000] Loss[3.237] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[1000] rmse=0.020968 lr=0.277977 +[1,0]:INFO:root:Epoch[103] Batch[1100] Loss[2.737] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[1100] rmse=0.020961 lr=0.277802 +[1,0]:INFO:root:Epoch[103] Batch[1200] Loss[5.054] +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[1200] rmse=0.020961 lr=0.277628 +[1,0]:INFO:root:Epoch[103] Rank[0] Batch[1251] Time cost=399.03 Train-metric=0.020969 +[1,0]:INFO:root:Epoch[103] Speed: 3210.32 samples/sec +[1,0]:INFO:root:Epoch[104] Batch[100] Loss[2.758] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[100] rmse=0.020884 lr=0.277364 +[1,0]:INFO:root:Epoch[104] Batch[200] Loss[4.810] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[200] rmse=0.020908 lr=0.277190 +[1,0]:INFO:root:Epoch[104] Batch[300] Loss[2.968] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[300] rmse=0.020816 lr=0.277015 +[1,0]:INFO:root:Epoch[104] Batch[400] Loss[4.690] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[400] rmse=0.020827 lr=0.276840 +[1,0]:INFO:root:Epoch[104] Batch[500] Loss[3.161] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[500] rmse=0.020838 lr=0.276665 +[1,0]:INFO:root:Epoch[104] Batch[600] Loss[2.757] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[600] rmse=0.020863 lr=0.276490 +[1,0]:INFO:root:Epoch[104] Batch[700] Loss[2.974] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[700] rmse=0.020912 lr=0.276315 +[1,0]:INFO:root:Epoch[104] Batch[800] Loss[3.143] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[800] rmse=0.020935 lr=0.276140 +[1,0]:INFO:root:Epoch[104] Batch[900] Loss[4.622] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[900] rmse=0.020952 lr=0.275965 +[1,0]:INFO:root:Epoch[104] Batch[1000] Loss[2.995] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[1000] rmse=0.020966 lr=0.275790 +[1,0]:INFO:root:Epoch[104] Batch[1100] Loss[3.637] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[1100] rmse=0.020974 lr=0.275615 +[1,0]:INFO:root:Epoch[104] Batch[1200] Loss[3.114] +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[1200] rmse=0.020981 lr=0.275439 +[1,0]:INFO:root:Epoch[104] Rank[0] Batch[1251] Time cost=399.46 Train-metric=0.020978 +[1,0]:INFO:root:Epoch[104] Speed: 3206.88 samples/sec +[1,0]:INFO:root:Epoch[104] Rank[0] Validation-accuracy=0.607660 Validation-top_k_accuracy_5=0.837200 +[1,0]:INFO:root:Epoch[105] Batch[100] Loss[2.737] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[100] rmse=0.020970 lr=0.275174 +[1,0]:INFO:root:Epoch[105] Batch[200] Loss[5.301] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[200] rmse=0.020889 lr=0.274999 +[1,0]:INFO:root:Epoch[105] Batch[300] Loss[2.895] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[300] rmse=0.020918 lr=0.274823 +[1,0]:INFO:root:Epoch[105] Batch[400] Loss[2.651] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[400] rmse=0.020912 lr=0.274648 +[1,0]:INFO:root:Epoch[105] Batch[500] Loss[2.999] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[500] rmse=0.020928 lr=0.274472 +[1,0]:INFO:root:Epoch[105] Batch[600] Loss[2.941] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[600] rmse=0.020917 lr=0.274296 +[1,0]:INFO:root:Epoch[105] Batch[700] Loss[5.005] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[700] rmse=0.020938 lr=0.274120 +[1,0]:INFO:root:Epoch[105] Batch[800] Loss[3.179] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[800] rmse=0.020942 lr=0.273944 +[1,0]:INFO:root:Epoch[105] Batch[900] Loss[2.827] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[900] rmse=0.020963 lr=0.273768 +[1,0]:INFO:root:Epoch[105] Batch[1000] Loss[3.255] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[1000] rmse=0.020948 lr=0.273592 +[1,0]:INFO:root:Epoch[105] Batch[1100] Loss[4.536] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[1100] rmse=0.020929 lr=0.273416 +[1,0]:INFO:root:Epoch[105] Batch[1200] Loss[4.820] +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[1200] rmse=0.020910 lr=0.273240 +[1,0]:INFO:root:Epoch[105] Rank[0] Batch[1251] Time cost=398.34 Train-metric=0.020915 +[1,0]:INFO:root:Epoch[105] Speed: 3215.90 samples/sec +[1,0]:INFO:root:Epoch[106] Batch[100] Loss[2.868] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[100] rmse=0.020839 lr=0.272974 +[1,0]:INFO:root:Epoch[106] Batch[200] Loss[3.422] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[200] rmse=0.020855 lr=0.272797 +[1,0]:INFO:root:Epoch[106] Batch[300] Loss[3.211] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[300] rmse=0.020928 lr=0.272621 +[1,0]:INFO:root:Epoch[106] Batch[400] Loss[2.939] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[400] rmse=0.020935 lr=0.272444 +[1,0]:INFO:root:Epoch[106] Batch[500] Loss[3.621] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[500] rmse=0.020931 lr=0.272268 +[1,0]:INFO:root:Epoch[106] Batch[600] Loss[2.964] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[600] rmse=0.020929 lr=0.272091 +[1,0]:INFO:root:Epoch[106] Batch[700] Loss[3.489] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[700] rmse=0.020912 lr=0.271915 +[1,0]:INFO:root:Epoch[106] Batch[800] Loss[3.013] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[800] rmse=0.020917 lr=0.271738 +[1,0]:INFO:root:Epoch[106] Batch[900] Loss[3.290] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[900] rmse=0.020888 lr=0.271561 +[1,0]:INFO:root:Epoch[106] Batch[1000] Loss[3.129] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[1000] rmse=0.020896 lr=0.271384 +[1,0]:INFO:root:Epoch[106] Batch[1100] Loss[2.896] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[1100] rmse=0.020886 lr=0.271207 +[1,0]:INFO:root:Epoch[106] Batch[1200] Loss[4.302] +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[1200] rmse=0.020877 lr=0.271030 +[1,0]:INFO:root:Epoch[106] Rank[0] Batch[1251] Time cost=399.39 Train-metric=0.020874 +[1,0]:INFO:root:Epoch[106] Speed: 3207.42 samples/sec +[1,0]:INFO:root:Epoch[107] Batch[100] Loss[4.217] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[100] rmse=0.020913 lr=0.270763 +[1,0]:INFO:root:Epoch[107] Batch[200] Loss[4.126] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[200] rmse=0.020893 lr=0.270586 +[1,0]:INFO:root:Epoch[107] Batch[300] Loss[4.230] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[300] rmse=0.020946 lr=0.270408 +[1,0]:INFO:root:Epoch[107] Batch[400] Loss[2.770] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[400] rmse=0.020945 lr=0.270231 +[1,0]:INFO:root:Epoch[107] Batch[500] Loss[3.030] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[500] rmse=0.020930 lr=0.270054 +[1,0]:INFO:root:Epoch[107] Batch[600] Loss[2.834] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[600] rmse=0.020917 lr=0.269876 +[1,0]:INFO:root:Epoch[107] Batch[700] Loss[2.855] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[700] rmse=0.020945 lr=0.269699 +[1,0]:INFO:root:Epoch[107] Batch[800] Loss[2.800] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[800] rmse=0.020941 lr=0.269521 +[1,0]:INFO:root:Epoch[107] Batch[900] Loss[3.170] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[900] rmse=0.020949 lr=0.269344 +[1,0]:INFO:root:Epoch[107] Batch[1000] Loss[3.057] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[1000] rmse=0.020940 lr=0.269166 +[1,0]:INFO:root:Epoch[107] Batch[1100] Loss[4.697] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[1100] rmse=0.020946 lr=0.268988 +[1,0]:INFO:root:Epoch[107] Batch[1200] Loss[3.001] +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[1200] rmse=0.020948 lr=0.268811 +[1,0]:INFO:root:Epoch[107] Rank[0] Batch[1251] Time cost=399.24 Train-metric=0.020949 +[1,0]:INFO:root:Epoch[107] Speed: 3208.64 samples/sec +[1,0]:INFO:root:Epoch[108] Batch[100] Loss[3.020] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[100] rmse=0.020682 lr=0.268542 +[1,0]:INFO:root:Epoch[108] Batch[200] Loss[3.139] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[200] rmse=0.020704 lr=0.268364 +[1,0]:INFO:root:Epoch[108] Batch[300] Loss[3.942] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[300] rmse=0.020676 lr=0.268186 +[1,0]:INFO:root:Epoch[108] Batch[400] Loss[5.282] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[400] rmse=0.020768 lr=0.268008 +[1,0]:INFO:root:Epoch[108] Batch[500] Loss[2.933] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[500] rmse=0.020809 lr=0.267830 +[1,0]:INFO:root:Epoch[108] Batch[600] Loss[2.788] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[600] rmse=0.020781 lr=0.267652 +[1,0]:INFO:root:Epoch[108] Batch[700] Loss[4.344] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[700] rmse=0.020782 lr=0.267473 +[1,0]:INFO:root:Epoch[108] Batch[800] Loss[2.943] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[800] rmse=0.020788 lr=0.267295 +[1,0]:INFO:root:Epoch[108] Batch[900] Loss[2.928] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[900] rmse=0.020801 lr=0.267117 +[1,0]:INFO:root:Epoch[108] Batch[1000] Loss[4.360] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[1000] rmse=0.020817 lr=0.266938 +[1,0]:INFO:root:Epoch[108] Batch[1100] Loss[2.971] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[1100] rmse=0.020826 lr=0.266760 +[1,0]:INFO:root:Epoch[108] Batch[1200] Loss[3.347] +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[1200] rmse=0.020817 lr=0.266581 +[1,0]:INFO:root:Epoch[108] Rank[0] Batch[1251] Time cost=399.25 Train-metric=0.020826 +[1,0]:INFO:root:Epoch[108] Speed: 3208.59 samples/sec +[1,0]:INFO:root:Epoch[109] Batch[100] Loss[2.965] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[100] rmse=0.020751 lr=0.266312 +[1,0]:INFO:root:Epoch[109] Batch[200] Loss[3.710] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[200] rmse=0.020818 lr=0.266133 +[1,0]:INFO:root:Epoch[109] Batch[300] Loss[5.219] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[300] rmse=0.020828 lr=0.265954 +[1,0]:INFO:root:Epoch[109] Batch[400] Loss[3.075] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[400] rmse=0.020847 lr=0.265775 +[1,0]:INFO:root:Epoch[109] Batch[500] Loss[2.708] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[500] rmse=0.020846 lr=0.265596 +[1,0]:INFO:root:Epoch[109] Batch[600] Loss[2.738] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[600] rmse=0.020854 lr=0.265418 +[1,0]:INFO:root:Epoch[109] Batch[700] Loss[3.198] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[700] rmse=0.020856 lr=0.265239 +[1,0]:INFO:root:Epoch[109] Batch[800] Loss[2.911] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[800] rmse=0.020876 lr=0.265060 +[1,0]:INFO:root:Epoch[109] Batch[900] Loss[3.237] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[900] rmse=0.020858 lr=0.264880 +[1,0]:INFO:root:Epoch[109] Batch[1000] Loss[3.660] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[1000] rmse=0.020877 lr=0.264701 +[1,0]:INFO:root:Epoch[109] Batch[1100] Loss[2.752] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[1100] rmse=0.020892 lr=0.264522 +[1,0]:INFO:root:Epoch[109] Batch[1200] Loss[2.625] +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[1200] rmse=0.020899 lr=0.264343 +[1,0]:INFO:root:Epoch[109] Rank[0] Batch[1251] Time cost=399.56 Train-metric=0.020897 +[1,0]:INFO:root:Epoch[109] Speed: 3206.05 samples/sec +[1,0]:INFO:root:Epoch[109] Rank[0] Validation-accuracy=0.618080 Validation-top_k_accuracy_5=0.847000 +[1,0]:INFO:root:Epoch[110] Batch[100] Loss[2.565] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[100] rmse=0.020692 lr=0.264072 +[1,0]:INFO:root:Epoch[110] Batch[200] Loss[3.428] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[200] rmse=0.020770 lr=0.263892 +[1,0]:INFO:root:Epoch[110] Batch[300] Loss[4.750] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[300] rmse=0.020745 lr=0.263713 +[1,0]:INFO:root:Epoch[110] Batch[400] Loss[2.616] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[400] rmse=0.020785 lr=0.263533 +[1,0]:INFO:root:Epoch[110] Batch[500] Loss[3.704] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[500] rmse=0.020741 lr=0.263354 +[1,0]:INFO:root:Epoch[110] Batch[600] Loss[4.241] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[600] rmse=0.020769 lr=0.263174 +[1,0]:INFO:root:Epoch[110] Batch[700] Loss[2.704] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[700] rmse=0.020789 lr=0.262995 +[1,0]:INFO:root:Epoch[110] Batch[800] Loss[2.825] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[800] rmse=0.020805 lr=0.262815 +[1,0]:INFO:root:Epoch[110] Batch[900] Loss[3.651] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[900] rmse=0.020823 lr=0.262635 +[1,0]:INFO:root:Epoch[110] Batch[1000] Loss[4.786] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[1000] rmse=0.020840 lr=0.262455 +[1,0]:INFO:root:Epoch[110] Batch[1100] Loss[3.201] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[1100] rmse=0.020833 lr=0.262275 +[1,0]:INFO:root:Epoch[110] Batch[1200] Loss[2.827] +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[1200] rmse=0.020825 lr=0.262095 +[1,0]:INFO:root:Epoch[110] Rank[0] Batch[1251] Time cost=399.61 Train-metric=0.020833 +[1,0]:INFO:root:Epoch[110] Speed: 3205.71 samples/sec +[1,0]:INFO:root:Epoch[111] Batch[100] Loss[4.803] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[100] rmse=0.021003 lr=0.261823 +[1,0]:INFO:root:Epoch[111] Batch[200] Loss[5.304] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[200] rmse=0.020892 lr=0.261643 +[1,0]:INFO:root:Epoch[111] Batch[300] Loss[2.768] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[300] rmse=0.020908 lr=0.261463 +[1,0]:INFO:root:Epoch[111] Batch[400] Loss[2.994] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[400] rmse=0.020852 lr=0.261283 +[1,0]:INFO:root:Epoch[111] Batch[500] Loss[2.842] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[500] rmse=0.020849 lr=0.261102 +[1,0]:INFO:root:Epoch[111] Batch[600] Loss[2.706] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[600] rmse=0.020830 lr=0.260922 +[1,0]:INFO:root:Epoch[111] Batch[700] Loss[3.082] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[700] rmse=0.020860 lr=0.260742 +[1,0]:INFO:root:Epoch[111] Batch[800] Loss[2.899] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[800] rmse=0.020853 lr=0.260561 +[1,0]:INFO:root:Epoch[111] Batch[900] Loss[2.955] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[900] rmse=0.020873 lr=0.260381 +[1,0]:INFO:root:Epoch[111] Batch[1000] Loss[2.910] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[1000] rmse=0.020897 lr=0.260200 +[1,0]:INFO:root:Epoch[111] Batch[1100] Loss[3.670] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[1100] rmse=0.020904 lr=0.260019 +[1,0]:INFO:root:Epoch[111] Batch[1200] Loss[4.618] +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[1200] rmse=0.020891 lr=0.259839 +[1,0]:INFO:root:Epoch[111] Rank[0] Batch[1251] Time cost=398.96 Train-metric=0.020887 +[1,0]:INFO:root:Epoch[111] Speed: 3210.89 samples/sec +[1,0]:INFO:root:Epoch[112] Batch[100] Loss[3.929] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[100] rmse=0.020796 lr=0.259566 +[1,0]:INFO:root:Epoch[112] Batch[200] Loss[3.736] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[200] rmse=0.020701 lr=0.259385 +[1,0]:INFO:root:Epoch[112] Batch[300] Loss[3.272] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[300] rmse=0.020721 lr=0.259204 +[1,0]:INFO:root:Epoch[112] Batch[400] Loss[4.531] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[400] rmse=0.020772 lr=0.259023 +[1,0]:INFO:root:Epoch[112] Batch[500] Loss[2.746] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[500] rmse=0.020800 lr=0.258842 +[1,0]:INFO:root:Epoch[112] Batch[600] Loss[3.205] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[600] rmse=0.020831 lr=0.258661 +[1,0]:INFO:root:Epoch[112] Batch[700] Loss[4.996] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[700] rmse=0.020790 lr=0.258480 +[1,0]:INFO:root:Epoch[112] Batch[800] Loss[2.911] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[800] rmse=0.020799 lr=0.258299 +[1,0]:INFO:root:Epoch[112] Batch[900] Loss[3.100] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[900] rmse=0.020811 lr=0.258118 +[1,0]:INFO:root:Epoch[112] Batch[1000] Loss[3.040] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[1000] rmse=0.020808 lr=0.257937 +[1,0]:INFO:root:Epoch[112] Batch[1100] Loss[2.850] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[1100] rmse=0.020807 lr=0.257755 +[1,0]:INFO:root:Epoch[112] Batch[1200] Loss[4.056] +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[1200] rmse=0.020809 lr=0.257574 +[1,0]:INFO:root:Epoch[112] Rank[0] Batch[1251] Time cost=398.79 Train-metric=0.020810 +[1,0]:INFO:root:Epoch[112] Speed: 3212.24 samples/sec +[1,0]:INFO:root:Epoch[113] Batch[100] Loss[3.305] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[100] rmse=0.020723 lr=0.257300 +[1,0]:INFO:root:Epoch[113] Batch[200] Loss[2.815] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[200] rmse=0.020729 lr=0.257119 +[1,0]:INFO:root:Epoch[113] Batch[300] Loss[2.791] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[300] rmse=0.020782 lr=0.256937 +[1,0]:INFO:root:Epoch[113] Batch[400] Loss[2.757] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[400] rmse=0.020805 lr=0.256756 +[1,0]:INFO:root:Epoch[113] Batch[500] Loss[3.653] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[500] rmse=0.020835 lr=0.256574 +[1,0]:INFO:root:Epoch[113] Batch[600] Loss[3.735] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[600] rmse=0.020843 lr=0.256392 +[1,0]:INFO:root:Epoch[113] Batch[700] Loss[2.936] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[700] rmse=0.020849 lr=0.256211 +[1,0]:INFO:root:Epoch[113] Batch[800] Loss[2.698] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[800] rmse=0.020841 lr=0.256029 +[1,0]:INFO:root:Epoch[113] Batch[900] Loss[4.029] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[900] rmse=0.020828 lr=0.255847 +[1,0]:INFO:root:Epoch[113] Batch[1000] Loss[4.879] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[1000] rmse=0.020814 lr=0.255665 +[1,0]:INFO:root:Epoch[113] Batch[1100] Loss[2.891] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[1100] rmse=0.020821 lr=0.255483 +[1,0]:INFO:root:Epoch[113] Batch[1200] Loss[2.945] +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[1200] rmse=0.020818 lr=0.255301 +[1,0]:INFO:root:Epoch[113] Rank[0] Batch[1251] Time cost=398.74 Train-metric=0.020808 +[1,0]:INFO:root:Epoch[113] Speed: 3212.70 samples/sec +[1,0]:INFO:root:Epoch[114] Batch[100] Loss[2.558] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[100] rmse=0.020579 lr=0.255026 +[1,0]:INFO:root:Epoch[114] Batch[200] Loss[2.705] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[200] rmse=0.020711 lr=0.254844 +[1,0]:INFO:root:Epoch[114] Batch[300] Loss[3.305] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[300] rmse=0.020686 lr=0.254662 +[1,0]:INFO:root:Epoch[114] Batch[400] Loss[4.736] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[400] rmse=0.020718 lr=0.254480 +[1,0]:INFO:root:Epoch[114] Batch[500] Loss[3.198] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[500] rmse=0.020705 lr=0.254298 +[1,0]:INFO:root:Epoch[114] Batch[600] Loss[5.161] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[600] rmse=0.020684 lr=0.254115 +[1,0]:INFO:root:Epoch[114] Batch[700] Loss[4.087] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[700] rmse=0.020717 lr=0.253933 +[1,0]:INFO:root:Epoch[114] Batch[800] Loss[5.397] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[800] rmse=0.020736 lr=0.253751 +[1,0]:INFO:root:Epoch[114] Batch[900] Loss[2.981] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[900] rmse=0.020737 lr=0.253568 +[1,0]:INFO:root:Epoch[114] Batch[1000] Loss[2.868] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[1000] rmse=0.020744 lr=0.253386 +[1,0]:INFO:root:Epoch[114] Batch[1100] Loss[4.421] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[1100] rmse=0.020748 lr=0.253203 +[1,0]:INFO:root:Epoch[114] Batch[1200] Loss[2.962] +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[1200] rmse=0.020745 lr=0.253021 +[1,0]:INFO:root:Epoch[114] Rank[0] Batch[1251] Time cost=399.05 Train-metric=0.020742 +[1,0]:INFO:root:Epoch[114] Speed: 3210.20 samples/sec +[1,0]:INFO:root:Epoch[114] Rank[0] Validation-accuracy=0.615780 Validation-top_k_accuracy_5=0.845040 +[1,0]:INFO:root:Epoch[115] Batch[100] Loss[2.896] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[100] rmse=0.020637 lr=0.252745 +[1,0]:INFO:root:Epoch[115] Batch[200] Loss[2.534] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[200] rmse=0.020676 lr=0.252562 +[1,0]:INFO:root:Epoch[115] Batch[300] Loss[2.667] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[300] rmse=0.020775 lr=0.252379 +[1,0]:INFO:root:Epoch[115] Batch[400] Loss[3.105] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[400] rmse=0.020784 lr=0.252197 +[1,0]:INFO:root:Epoch[115] Batch[500] Loss[3.191] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[500] rmse=0.020764 lr=0.252014 +[1,0]:INFO:root:Epoch[115] Batch[600] Loss[2.726] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[600] rmse=0.020791 lr=0.251831 +[1,0]:INFO:root:Epoch[115] Batch[700] Loss[4.576] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[700] rmse=0.020790 lr=0.251648 +[1,0]:INFO:root:Epoch[115] Batch[800] Loss[2.931] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[800] rmse=0.020797 lr=0.251465 +[1,0]:INFO:root:Epoch[115] Batch[900] Loss[3.381] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[900] rmse=0.020822 lr=0.251282 +[1,0]:INFO:root:Epoch[115] Batch[1000] Loss[2.839] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[1000] rmse=0.020817 lr=0.251099 +[1,0]:INFO:root:Epoch[115] Batch[1100] Loss[4.743] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[1100] rmse=0.020832 lr=0.250916 +[1,0]:INFO:root:Epoch[115] Batch[1200] Loss[3.049] +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[1200] rmse=0.020836 lr=0.250733 +[1,0]:INFO:root:Epoch[115] Rank[0] Batch[1251] Time cost=398.37 Train-metric=0.020836 +[1,0]:INFO:root:Epoch[115] Speed: 3215.65 samples/sec +[1,0]:INFO:root:Epoch[116] Batch[100] Loss[2.728] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[100] rmse=0.020723 lr=0.250456 +[1,0]:INFO:root:Epoch[116] Batch[200] Loss[4.684] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[200] rmse=0.020723 lr=0.250273 +[1,0]:INFO:root:Epoch[116] Batch[300] Loss[5.020] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[300] rmse=0.020709 lr=0.250089 +[1,0]:INFO:root:Epoch[116] Batch[400] Loss[3.801] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[400] rmse=0.020749 lr=0.249906 +[1,0]:INFO:root:Epoch[116] Batch[500] Loss[2.893] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[500] rmse=0.020762 lr=0.249723 +[1,0]:INFO:root:Epoch[116] Batch[600] Loss[2.690] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[600] rmse=0.020769 lr=0.249539 +[1,0]:INFO:root:Epoch[116] Batch[700] Loss[2.774] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[700] rmse=0.020755 lr=0.249356 +[1,0]:INFO:root:Epoch[116] Batch[800] Loss[4.044] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[800] rmse=0.020756 lr=0.249172 +[1,0]:INFO:root:Epoch[116] Batch[900] Loss[2.756] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[900] rmse=0.020770 lr=0.248988 +[1,0]:INFO:root:Epoch[116] Batch[1000] Loss[4.817] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[1000] rmse=0.020770 lr=0.248805 +[1,0]:INFO:root:Epoch[116] Batch[1100] Loss[2.858] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[1100] rmse=0.020798 lr=0.248621 +[1,0]:INFO:root:Epoch[116] Batch[1200] Loss[5.266] +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[1200] rmse=0.020804 lr=0.248437 +[1,0]:INFO:root:Epoch[116] Rank[0] Batch[1251] Time cost=399.82 Train-metric=0.020806 +[1,0]:INFO:root:Epoch[116] Speed: 3204.00 samples/sec +[1,0]:INFO:root:Epoch[117] Batch[100] Loss[2.884] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[100] rmse=0.020768 lr=0.248160 +[1,0]:INFO:root:Epoch[117] Batch[200] Loss[4.880] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[200] rmse=0.020747 lr=0.247976 +[1,0]:INFO:root:Epoch[117] Batch[300] Loss[3.722] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[300] rmse=0.020801 lr=0.247792 +[1,0]:INFO:root:Epoch[117] Batch[400] Loss[2.711] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[400] rmse=0.020776 lr=0.247608 +[1,0]:INFO:root:Epoch[117] Batch[500] Loss[3.696] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[500] rmse=0.020799 lr=0.247424 +[1,0]:INFO:root:Epoch[117] Batch[600] Loss[3.060] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[600] rmse=0.020763 lr=0.247240 +[1,0]:INFO:root:Epoch[117] Batch[700] Loss[4.458] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[700] rmse=0.020780 lr=0.247056 +[1,0]:INFO:root:Epoch[117] Batch[800] Loss[5.156] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[800] rmse=0.020782 lr=0.246872 +[1,0]:INFO:root:Epoch[117] Batch[900] Loss[2.957] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[900] rmse=0.020808 lr=0.246688 +[1,0]:INFO:root:Epoch[117] Batch[1000] Loss[4.821] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[1000] rmse=0.020792 lr=0.246504 +[1,0]:INFO:root:Epoch[117] Batch[1100] Loss[3.195] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[1100] rmse=0.020789 lr=0.246320 +[1,0]:INFO:root:Epoch[117] Batch[1200] Loss[2.641] +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[1200] rmse=0.020803 lr=0.246136 +[1,0]:INFO:root:Epoch[117] Rank[0] Batch[1251] Time cost=399.75 Train-metric=0.020820 +[1,0]:INFO:root:Epoch[117] Speed: 3204.57 samples/sec +[1,0]:INFO:root:Epoch[118] Batch[100] Loss[2.710] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[100] rmse=0.020881 lr=0.245857 +[1,0]:INFO:root:Epoch[118] Batch[200] Loss[3.210] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[200] rmse=0.020797 lr=0.245673 +[1,0]:INFO:root:Epoch[118] Batch[300] Loss[4.836] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[300] rmse=0.020731 lr=0.245488 +[1,0]:INFO:root:Epoch[118] Batch[400] Loss[2.739] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[400] rmse=0.020721 lr=0.245304 +[1,0]:INFO:root:Epoch[118] Batch[500] Loss[2.836] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[500] rmse=0.020731 lr=0.245120 +[1,0]:INFO:root:Epoch[118] Batch[600] Loss[3.016] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[600] rmse=0.020758 lr=0.244935 +[1,0]:INFO:root:Epoch[118] Batch[700] Loss[3.161] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[700] rmse=0.020749 lr=0.244751 +[1,0]:INFO:root:Epoch[118] Batch[800] Loss[2.973] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[800] rmse=0.020741 lr=0.244566 +[1,0]:INFO:root:Epoch[118] Batch[900] Loss[3.143] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[900] rmse=0.020765 lr=0.244381 +[1,0]:INFO:root:Epoch[118] Batch[1000] Loss[3.102] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[1000] rmse=0.020764 lr=0.244197 +[1,0]:INFO:root:Epoch[118] Batch[1100] Loss[2.981] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[1100] rmse=0.020785 lr=0.244012 +[1,0]:INFO:root:Epoch[118] Batch[1200] Loss[4.288] +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[1200] rmse=0.020787 lr=0.243827 +[1,0]:INFO:root:Epoch[118] Rank[0] Batch[1251] Time cost=398.96 Train-metric=0.020789 +[1,0]:INFO:root:Epoch[118] Speed: 3210.88 samples/sec +[1,0]:INFO:root:Epoch[119] Batch[100] Loss[2.782] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[100] rmse=0.020557 lr=0.243548 +[1,0]:INFO:root:Epoch[119] Batch[200] Loss[2.671] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[200] rmse=0.020632 lr=0.243363 +[1,0]:INFO:root:Epoch[119] Batch[300] Loss[3.082] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[300] rmse=0.020698 lr=0.243178 +[1,0]:INFO:root:Epoch[119] Batch[400] Loss[5.082] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[400] rmse=0.020691 lr=0.242993 +[1,0]:INFO:root:Epoch[119] Batch[500] Loss[3.179] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[500] rmse=0.020717 lr=0.242808 +[1,0]:INFO:root:Epoch[119] Batch[600] Loss[2.786] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[600] rmse=0.020704 lr=0.242623 +[1,0]:INFO:root:Epoch[119] Batch[700] Loss[2.836] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[700] rmse=0.020705 lr=0.242438 +[1,0]:INFO:root:Epoch[119] Batch[800] Loss[2.692] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[800] rmse=0.020684 lr=0.242253 +[1,0]:INFO:root:Epoch[119] Batch[900] Loss[2.704] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[900] rmse=0.020691 lr=0.242068 +[1,0]:INFO:root:Epoch[119] Batch[1000] Loss[2.789] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[1000] rmse=0.020710 lr=0.241883 +[1,0]:INFO:root:Epoch[119] Batch[1100] Loss[3.921] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[1100] rmse=0.020740 lr=0.241698 +[1,0]:INFO:root:Epoch[119] Batch[1200] Loss[2.745] +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[1200] rmse=0.020741 lr=0.241513 +[1,0]:INFO:root:Epoch[119] Rank[0] Batch[1251] Time cost=398.93 Train-metric=0.020749 +[1,0]:INFO:root:Epoch[119] Speed: 3211.12 samples/sec +[1,0]:INFO:root:Epoch[119] Rank[0] Validation-accuracy=0.625240 Validation-top_k_accuracy_5=0.851320 +[1,0]:INFO:root:Epoch[120] Batch[100] Loss[3.525] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[100] rmse=0.020804 lr=0.241233 +[1,0]:INFO:root:Epoch[120] Batch[200] Loss[3.359] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[200] rmse=0.020859 lr=0.241047 +[1,0]:INFO:root:Epoch[120] Batch[300] Loss[5.126] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[300] rmse=0.020857 lr=0.240862 +[1,0]:INFO:root:Epoch[120] Batch[400] Loss[3.322] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[400] rmse=0.020807 lr=0.240677 +[1,0]:INFO:root:Epoch[120] Batch[500] Loss[4.615] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[500] rmse=0.020773 lr=0.240491 +[1,0]:INFO:root:Epoch[120] Batch[600] Loss[2.887] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[600] rmse=0.020764 lr=0.240306 +[1,0]:INFO:root:Epoch[120] Batch[700] Loss[5.239] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[700] rmse=0.020733 lr=0.240120 +[1,0]:INFO:root:Epoch[120] Batch[800] Loss[2.835] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[800] rmse=0.020745 lr=0.239935 +[1,0]:INFO:root:Epoch[120] Batch[900] Loss[3.168] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[900] rmse=0.020739 lr=0.239749 +[1,0]:INFO:root:Epoch[120] Batch[1000] Loss[3.679] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[1000] rmse=0.020733 lr=0.239564 +[1,0]:INFO:root:Epoch[120] Batch[1100] Loss[2.856] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[1100] rmse=0.020725 lr=0.239378 +[1,0]:INFO:root:Epoch[120] Batch[1200] Loss[3.223] +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[1200] rmse=0.020727 lr=0.239192 +[1,0]:INFO:root:Epoch[120] Rank[0] Batch[1251] Time cost=399.33 Train-metric=0.020726 +[1,0]:INFO:root:Epoch[120] Speed: 3207.90 samples/sec +[1,0]:INFO:root:Epoch[121] Batch[100] Loss[2.973] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[100] rmse=0.020737 lr=0.238912 +[1,0]:INFO:root:Epoch[121] Batch[200] Loss[2.796] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[200] rmse=0.020774 lr=0.238726 +[1,0]:INFO:root:Epoch[121] Batch[300] Loss[2.802] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[300] rmse=0.020705 lr=0.238540 +[1,0]:INFO:root:Epoch[121] Batch[400] Loss[5.272] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[400] rmse=0.020665 lr=0.238354 +[1,0]:INFO:root:Epoch[121] Batch[500] Loss[3.437] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[500] rmse=0.020655 lr=0.238168 +[1,0]:INFO:root:Epoch[121] Batch[600] Loss[2.865] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[600] rmse=0.020644 lr=0.237982 +[1,0]:INFO:root:Epoch[121] Batch[700] Loss[4.026] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[700] rmse=0.020641 lr=0.237797 +[1,0]:INFO:root:Epoch[121] Batch[800] Loss[4.513] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[800] rmse=0.020677 lr=0.237611 +[1,0]:INFO:root:Epoch[121] Batch[900] Loss[2.855] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[900] rmse=0.020686 lr=0.237425 +[1,0]:INFO:root:Epoch[121] Batch[1000] Loss[3.302] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[1000] rmse=0.020684 lr=0.237238 +[1,0]:INFO:root:Epoch[121] Batch[1100] Loss[2.821] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[1100] rmse=0.020685 lr=0.237052 +[1,0]:INFO:root:Epoch[121] Batch[1200] Loss[5.108] +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[1200] rmse=0.020692 lr=0.236866 +[1,0]:INFO:root:Epoch[121] Rank[0] Batch[1251] Time cost=402.32 Train-metric=0.020700 +[1,0]:INFO:root:Epoch[121] Speed: 3184.12 samples/sec +[1,0]:INFO:root:Epoch[122] Batch[100] Loss[2.950] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[100] rmse=0.020475 lr=0.236585 +[1,0]:INFO:root:Epoch[122] Batch[200] Loss[2.562] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[200] rmse=0.020519 lr=0.236399 +[1,0]:INFO:root:Epoch[122] Batch[300] Loss[2.711] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[300] rmse=0.020577 lr=0.236213 +[1,0]:INFO:root:Epoch[122] Batch[400] Loss[2.927] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[400] rmse=0.020601 lr=0.236027 +[1,0]:INFO:root:Epoch[122] Batch[500] Loss[2.771] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[500] rmse=0.020654 lr=0.235840 +[1,0]:INFO:root:Epoch[122] Batch[600] Loss[2.768] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[600] rmse=0.020652 lr=0.235654 +[1,0]:INFO:root:Epoch[122] Batch[700] Loss[5.108] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[700] rmse=0.020667 lr=0.235468 +[1,0]:INFO:root:Epoch[122] Batch[800] Loss[2.812] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[800] rmse=0.020651 lr=0.235281 +[1,0]:INFO:root:Epoch[122] Batch[900] Loss[2.712] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[900] rmse=0.020657 lr=0.235095 +[1,0]:INFO:root:Epoch[122] Batch[1000] Loss[5.167] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[1000] rmse=0.020649 lr=0.234908 +[1,0]:INFO:root:Epoch[122] Batch[1100] Loss[3.191] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[1100] rmse=0.020658 lr=0.234722 +[1,0]:INFO:root:Epoch[122] Batch[1200] Loss[3.367] +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[1200] rmse=0.020673 lr=0.234535 +[1,0]:INFO:root:Epoch[122] Rank[0] Batch[1251] Time cost=402.27 Train-metric=0.020667 +[1,0]:INFO:root:Epoch[122] Speed: 3184.52 samples/sec +[1,0]:INFO:root:Epoch[123] Batch[100] Loss[2.923] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[100] rmse=0.020532 lr=0.234254 +[1,0]:INFO:root:Epoch[123] Batch[200] Loss[2.651] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[200] rmse=0.020560 lr=0.234067 +[1,0]:INFO:root:Epoch[123] Batch[300] Loss[2.852] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[300] rmse=0.020538 lr=0.233880 +[1,0]:INFO:root:Epoch[123] Batch[400] Loss[2.815] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[400] rmse=0.020601 lr=0.233694 +[1,0]:INFO:root:Epoch[123] Batch[500] Loss[2.828] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[500] rmse=0.020624 lr=0.233507 +[1,0]:INFO:root:Epoch[123] Batch[600] Loss[5.290] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[600] rmse=0.020605 lr=0.233320 +[1,0]:INFO:root:Epoch[123] Batch[700] Loss[2.948] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[700] rmse=0.020618 lr=0.233134 +[1,0]:INFO:root:Epoch[123] Batch[800] Loss[3.394] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[800] rmse=0.020611 lr=0.232947 +[1,0]:INFO:root:Epoch[123] Batch[900] Loss[4.895] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[900] rmse=0.020652 lr=0.232760 +[1,0]:INFO:root:Epoch[123] Batch[1000] Loss[4.918] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[1000] rmse=0.020675 lr=0.232573 +[1,0]:INFO:root:Epoch[123] Batch[1100] Loss[4.947] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[1100] rmse=0.020662 lr=0.232386 +[1,0]:INFO:root:Epoch[123] Batch[1200] Loss[3.793] +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[1200] rmse=0.020679 lr=0.232199 +[1,0]:INFO:root:Epoch[123] Rank[0] Batch[1251] Time cost=399.56 Train-metric=0.020695 +[1,0]:INFO:root:Epoch[123] Speed: 3206.12 samples/sec +[1,0]:INFO:root:Epoch[124] Batch[100] Loss[3.993] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[100] rmse=0.020621 lr=0.231917 +[1,0]:INFO:root:Epoch[124] Batch[200] Loss[2.720] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[200] rmse=0.020564 lr=0.231730 +[1,0]:INFO:root:Epoch[124] Batch[300] Loss[2.915] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[300] rmse=0.020637 lr=0.231543 +[1,0]:INFO:root:Epoch[124] Batch[400] Loss[2.749] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[400] rmse=0.020632 lr=0.231356 +[1,0]:INFO:root:Epoch[124] Batch[500] Loss[2.815] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[500] rmse=0.020644 lr=0.231169 +[1,0]:INFO:root:Epoch[124] Batch[600] Loss[2.857] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[600] rmse=0.020648 lr=0.230982 +[1,0]:INFO:root:Epoch[124] Batch[700] Loss[3.067] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[700] rmse=0.020656 lr=0.230795 +[1,0]:INFO:root:Epoch[124] Batch[800] Loss[3.161] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[800] rmse=0.020645 lr=0.230608 +[1,0]:INFO:root:Epoch[124] Batch[900] Loss[3.416] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[900] rmse=0.020648 lr=0.230421 +[1,0]:INFO:root:Epoch[124] Batch[1000] Loss[3.957] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[1000] rmse=0.020651 lr=0.230233 +[1,0]:INFO:root:Epoch[124] Batch[1100] Loss[4.886] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[1100] rmse=0.020642 lr=0.230046 +[1,0]:INFO:root:Epoch[124] Batch[1200] Loss[2.501] +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[1200] rmse=0.020661 lr=0.229859 +[1,0]:INFO:root:Epoch[124] Rank[0] Batch[1251] Time cost=400.19 Train-metric=0.020665 +[1,0]:INFO:root:Epoch[124] Speed: 3201.08 samples/sec +[1,0]:INFO:root:Epoch[124] Rank[0] Validation-accuracy=0.621100 Validation-top_k_accuracy_5=0.848380 +[1,0]:INFO:root:Epoch[125] Batch[100] Loss[2.947] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[100] rmse=0.020766 lr=0.229576 +[1,0]:INFO:root:Epoch[125] Batch[200] Loss[3.553] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[200] rmse=0.020650 lr=0.229389 +[1,0]:INFO:root:Epoch[125] Batch[300] Loss[3.032] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[300] rmse=0.020644 lr=0.229201 +[1,0]:INFO:root:Epoch[125] Batch[400] Loss[3.044] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[400] rmse=0.020653 lr=0.229014 +[1,0]:INFO:root:Epoch[125] Batch[500] Loss[3.154] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[500] rmse=0.020620 lr=0.228827 +[1,0]:INFO:root:Epoch[125] Batch[600] Loss[4.434] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[600] rmse=0.020644 lr=0.228639 +[1,0]:INFO:root:Epoch[125] Batch[700] Loss[2.596] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[700] rmse=0.020674 lr=0.228452 +[1,0]:INFO:root:Epoch[125] Batch[800] Loss[4.445] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[800] rmse=0.020672 lr=0.228264 +[1,0]:INFO:root:Epoch[125] Batch[900] Loss[3.486] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[900] rmse=0.020682 lr=0.228077 +[1,0]:INFO:root:Epoch[125] Batch[1000] Loss[2.853] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[1000] rmse=0.020678 lr=0.227889 +[1,0]:INFO:root:Epoch[125] Batch[1100] Loss[3.769] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[1100] rmse=0.020695 lr=0.227702 +[1,0]:INFO:root:Epoch[125] Batch[1200] Loss[4.128] +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[1200] rmse=0.020700 lr=0.227514 +[1,0]:INFO:root:Epoch[125] Rank[0] Batch[1251] Time cost=399.05 Train-metric=0.020696 +[1,0]:INFO:root:Epoch[125] Speed: 3210.16 samples/sec +[1,0]:INFO:root:Epoch[126] Batch[100] Loss[3.064] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[100] rmse=0.020212 lr=0.227231 +[1,0]:INFO:root:Epoch[126] Batch[200] Loss[4.627] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[200] rmse=0.020406 lr=0.227043 +[1,0]:INFO:root:Epoch[126] Batch[300] Loss[2.569] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[300] rmse=0.020445 lr=0.226856 +[1,0]:INFO:root:Epoch[126] Batch[400] Loss[3.429] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[400] rmse=0.020471 lr=0.226668 +[1,0]:INFO:root:Epoch[126] Batch[500] Loss[2.748] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[500] rmse=0.020519 lr=0.226480 +[1,0]:INFO:root:Epoch[126] Batch[600] Loss[2.785] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[600] rmse=0.020539 lr=0.226293 +[1,0]:INFO:root:Epoch[126] Batch[700] Loss[4.884] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[700] rmse=0.020544 lr=0.226105 +[1,0]:INFO:root:Epoch[126] Batch[800] Loss[5.023] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[800] rmse=0.020553 lr=0.225917 +[1,0]:INFO:root:Epoch[126] Batch[900] Loss[3.068] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[900] rmse=0.020587 lr=0.225729 +[1,0]:INFO:root:Epoch[126] Batch[1000] Loss[5.411] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[1000] rmse=0.020620 lr=0.225542 +[1,0]:INFO:root:Epoch[126] Batch[1100] Loss[4.314] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[1100] rmse=0.020632 lr=0.225354 +[1,0]:INFO:root:Epoch[126] Batch[1200] Loss[5.297] +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[1200] rmse=0.020635 lr=0.225166 +[1,0]:INFO:root:Epoch[126] Rank[0] Batch[1251] Time cost=398.59 Train-metric=0.020641 +[1,0]:INFO:root:Epoch[126] Speed: 3213.91 samples/sec +[1,0]:INFO:root:Epoch[127] Batch[100] Loss[2.885] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[100] rmse=0.020411 lr=0.224882 +[1,0]:INFO:root:Epoch[127] Batch[200] Loss[3.019] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[200] rmse=0.020532 lr=0.224694 +[1,0]:INFO:root:Epoch[127] Batch[300] Loss[4.956] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[300] rmse=0.020539 lr=0.224506 +[1,0]:INFO:root:Epoch[127] Batch[400] Loss[3.798] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[400] rmse=0.020592 lr=0.224318 +[1,0]:INFO:root:Epoch[127] Batch[500] Loss[4.537] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[500] rmse=0.020569 lr=0.224130 +[1,0]:INFO:root:Epoch[127] Batch[600] Loss[4.720] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[600] rmse=0.020574 lr=0.223942 +[1,0]:INFO:root:Epoch[127] Batch[700] Loss[3.216] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[700] rmse=0.020589 lr=0.223754 +[1,0]:INFO:root:Epoch[127] Batch[800] Loss[3.120] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[800] rmse=0.020616 lr=0.223566 +[1,0]:INFO:root:Epoch[127] Batch[900] Loss[2.716] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[900] rmse=0.020625 lr=0.223378 +[1,0]:INFO:root:Epoch[127] Batch[1000] Loss[5.124] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[1000] rmse=0.020632 lr=0.223190 +[1,0]:INFO:root:Epoch[127] Batch[1100] Loss[3.152] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[1100] rmse=0.020645 lr=0.223002 +[1,0]:INFO:root:Epoch[127] Batch[1200] Loss[2.823] +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[1200] rmse=0.020643 lr=0.222814 +[1,0]:INFO:root:Epoch[127] Rank[0] Batch[1251] Time cost=399.06 Train-metric=0.020642 +[1,0]:INFO:root:Epoch[127] Speed: 3210.14 samples/sec +[1,0]:INFO:root:Epoch[128] Batch[100] Loss[4.015] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[100] rmse=0.020733 lr=0.222530 +[1,0]:INFO:root:Epoch[128] Batch[200] Loss[2.924] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[200] rmse=0.020638 lr=0.222342 +[1,0]:INFO:root:Epoch[128] Batch[300] Loss[3.182] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[300] rmse=0.020578 lr=0.222153 +[1,0]:INFO:root:Epoch[128] Batch[400] Loss[3.418] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[400] rmse=0.020628 lr=0.221965 +[1,0]:INFO:root:Epoch[128] Batch[500] Loss[4.656] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[500] rmse=0.020553 lr=0.221777 +[1,0]:INFO:root:Epoch[128] Batch[600] Loss[3.384] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[600] rmse=0.020524 lr=0.221589 +[1,0]:INFO:root:Epoch[128] Batch[700] Loss[2.936] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[700] rmse=0.020548 lr=0.221400 +[1,0]:INFO:root:Epoch[128] Batch[800] Loss[2.570] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[800] rmse=0.020564 lr=0.221212 +[1,0]:INFO:root:Epoch[128] Batch[900] Loss[3.013] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[900] rmse=0.020580 lr=0.221024 +[1,0]:INFO:root:Epoch[128] Batch[1000] Loss[3.570] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[1000] rmse=0.020602 lr=0.220835 +[1,0]:INFO:root:Epoch[128] Batch[1100] Loss[2.744] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[1100] rmse=0.020605 lr=0.220647 +[1,0]:INFO:root:Epoch[128] Batch[1200] Loss[2.803] +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[1200] rmse=0.020608 lr=0.220459 +[1,0]:INFO:root:Epoch[128] Rank[0] Batch[1251] Time cost=398.84 Train-metric=0.020613 +[1,0]:INFO:root:Epoch[128] Speed: 3211.84 samples/sec +[1,0]:INFO:root:Epoch[129] Batch[100] Loss[5.083] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[100] rmse=0.020456 lr=0.220174 +[1,0]:INFO:root:Epoch[129] Batch[200] Loss[3.125] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[200] rmse=0.020497 lr=0.219986 +[1,0]:INFO:root:Epoch[129] Batch[300] Loss[4.845] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[300] rmse=0.020569 lr=0.219797 +[1,0]:INFO:root:Epoch[129] Batch[400] Loss[2.807] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[400] rmse=0.020590 lr=0.219609 +[1,0]:INFO:root:Epoch[129] Batch[500] Loss[3.176] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[500] rmse=0.020585 lr=0.219420 +[1,0]:INFO:root:Epoch[129] Batch[600] Loss[3.009] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[600] rmse=0.020610 lr=0.219232 +[1,0]:INFO:root:Epoch[129] Batch[700] Loss[2.891] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[700] rmse=0.020615 lr=0.219043 +[1,0]:INFO:root:Epoch[129] Batch[800] Loss[3.220] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[800] rmse=0.020629 lr=0.218855 +[1,0]:INFO:root:Epoch[129] Batch[900] Loss[3.927] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[900] rmse=0.020638 lr=0.218666 +[1,0]:INFO:root:Epoch[129] Batch[1000] Loss[3.477] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[1000] rmse=0.020635 lr=0.218478 +[1,0]:INFO:root:Epoch[129] Batch[1100] Loss[2.991] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[1100] rmse=0.020640 lr=0.218289 +[1,0]:INFO:root:Epoch[129] Batch[1200] Loss[2.818] +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[1200] rmse=0.020633 lr=0.218101 +[1,0]:INFO:root:Epoch[129] Rank[0] Batch[1251] Time cost=399.58 Train-metric=0.020636 +[1,0]:INFO:root:Epoch[129] Speed: 3205.91 samples/sec +[1,0]:INFO:root:Epoch[129] Rank[0] Validation-accuracy=0.626560 Validation-top_k_accuracy_5=0.855000 +[1,0]:INFO:root:Epoch[130] Batch[100] Loss[2.752] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[100] rmse=0.020431 lr=0.217816 +[1,0]:INFO:root:Epoch[130] Batch[200] Loss[4.392] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[200] rmse=0.020531 lr=0.217627 +[1,0]:INFO:root:Epoch[130] Batch[300] Loss[4.735] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[300] rmse=0.020550 lr=0.217438 +[1,0]:INFO:root:Epoch[130] Batch[400] Loss[2.998] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[400] rmse=0.020563 lr=0.217250 +[1,0]:INFO:root:Epoch[130] Batch[500] Loss[3.088] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[500] rmse=0.020578 lr=0.217061 +[1,0]:INFO:root:Epoch[130] Batch[600] Loss[2.999] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[600] rmse=0.020596 lr=0.216872 +[1,0]:INFO:root:Epoch[130] Batch[700] Loss[2.308] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[700] rmse=0.020613 lr=0.216684 +[1,0]:INFO:root:Epoch[130] Batch[800] Loss[3.819] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[800] rmse=0.020664 lr=0.216495 +[1,0]:INFO:root:Epoch[130] Batch[900] Loss[4.128] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[900] rmse=0.020650 lr=0.216306 +[1,0]:INFO:root:Epoch[130] Batch[1000] Loss[2.948] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[1000] rmse=0.020640 lr=0.216118 +[1,0]:INFO:root:Epoch[130] Batch[1100] Loss[4.915] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[1100] rmse=0.020642 lr=0.215929 +[1,0]:INFO:root:Epoch[130] Batch[1200] Loss[2.979] +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[1200] rmse=0.020650 lr=0.215740 +[1,0]:INFO:root:Epoch[130] Rank[0] Batch[1251] Time cost=398.55 Train-metric=0.020646 +[1,0]:INFO:root:Epoch[130] Speed: 3214.24 samples/sec +[1,0]:INFO:root:Epoch[131] Batch[100] Loss[2.979] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[100] rmse=0.020655 lr=0.215455 +[1,0]:INFO:root:Epoch[131] Batch[200] Loss[2.870] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[200] rmse=0.020476 lr=0.215266 +[1,0]:INFO:root:Epoch[131] Batch[300] Loss[2.849] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[300] rmse=0.020570 lr=0.215077 +[1,0]:INFO:root:Epoch[131] Batch[400] Loss[5.382] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[400] rmse=0.020543 lr=0.214888 +[1,0]:INFO:root:Epoch[131] Batch[500] Loss[2.620] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[500] rmse=0.020536 lr=0.214700 +[1,0]:INFO:root:Epoch[131] Batch[600] Loss[2.815] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[600] rmse=0.020531 lr=0.214511 +[1,0]:INFO:root:Epoch[131] Batch[700] Loss[2.549] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[700] rmse=0.020530 lr=0.214322 +[1,0]:INFO:root:Epoch[131] Batch[800] Loss[2.884] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[800] rmse=0.020533 lr=0.214133 +[1,0]:INFO:root:Epoch[131] Batch[900] Loss[5.264] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[900] rmse=0.020551 lr=0.213944 +[1,0]:INFO:root:Epoch[131] Batch[1000] Loss[4.917] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[1000] rmse=0.020562 lr=0.213755 +[1,0]:INFO:root:Epoch[131] Batch[1100] Loss[3.244] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[1100] rmse=0.020552 lr=0.213566 +[1,0]:INFO:root:Epoch[131] Batch[1200] Loss[3.049] +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[1200] rmse=0.020572 lr=0.213377 +[1,0]:INFO:root:Epoch[131] Rank[0] Batch[1251] Time cost=398.97 Train-metric=0.020573 +[1,0]:INFO:root:Epoch[131] Speed: 3210.85 samples/sec +[1,0]:INFO:root:Epoch[132] Batch[100] Loss[4.977] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[100] rmse=0.020711 lr=0.213092 +[1,0]:INFO:root:Epoch[132] Batch[200] Loss[4.915] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[200] rmse=0.020656 lr=0.212903 +[1,0]:INFO:root:Epoch[132] Batch[300] Loss[3.104] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[300] rmse=0.020629 lr=0.212714 +[1,0]:INFO:root:Epoch[132] Batch[400] Loss[3.623] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[400] rmse=0.020616 lr=0.212525 +[1,0]:INFO:root:Epoch[132] Batch[500] Loss[3.995] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[500] rmse=0.020541 lr=0.212336 +[1,0]:INFO:root:Epoch[132] Batch[600] Loss[2.541] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[600] rmse=0.020556 lr=0.212147 +[1,0]:INFO:root:Epoch[132] Batch[700] Loss[2.840] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[700] rmse=0.020547 lr=0.211958 +[1,0]:INFO:root:Epoch[132] Batch[800] Loss[4.673] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[800] rmse=0.020560 lr=0.211769 +[1,0]:INFO:root:Epoch[132] Batch[900] Loss[2.954] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[900] rmse=0.020581 lr=0.211580 +[1,0]:INFO:root:Epoch[132] Batch[1000] Loss[4.423] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[1000] rmse=0.020578 lr=0.211391 +[1,0]:INFO:root:Epoch[132] Batch[1100] Loss[2.964] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[1100] rmse=0.020599 lr=0.211202 +[1,0]:INFO:root:Epoch[132] Batch[1200] Loss[2.993] +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[1200] rmse=0.020608 lr=0.211012 +[1,0]:INFO:root:Epoch[132] Rank[0] Batch[1251] Time cost=399.24 Train-metric=0.020609 +[1,0]:INFO:root:Epoch[132] Speed: 3208.69 samples/sec +[1,0]:INFO:root:Epoch[133] Batch[100] Loss[3.051] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[100] rmse=0.020667 lr=0.210727 +[1,0]:INFO:root:Epoch[133] Batch[200] Loss[4.816] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[200] rmse=0.020556 lr=0.210538 +[1,0]:INFO:root:Epoch[133] Batch[300] Loss[5.240] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[300] rmse=0.020536 lr=0.210349 +[1,0]:INFO:root:Epoch[133] Batch[400] Loss[3.667] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[400] rmse=0.020587 lr=0.210160 +[1,0]:INFO:root:Epoch[133] Batch[500] Loss[2.564] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[500] rmse=0.020576 lr=0.209970 +[1,0]:INFO:root:Epoch[133] Batch[600] Loss[2.997] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[600] rmse=0.020563 lr=0.209781 +[1,0]:INFO:root:Epoch[133] Batch[700] Loss[5.187] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[700] rmse=0.020567 lr=0.209592 +[1,0]:INFO:root:Epoch[133] Batch[800] Loss[3.047] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[800] rmse=0.020582 lr=0.209403 +[1,0]:INFO:root:Epoch[133] Batch[900] Loss[5.049] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[900] rmse=0.020558 lr=0.209214 +[1,0]:INFO:root:Epoch[133] Batch[1000] Loss[3.129] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[1000] rmse=0.020548 lr=0.209025 +[1,0]:INFO:root:Epoch[133] Batch[1100] Loss[2.732] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[1100] rmse=0.020567 lr=0.208835 +[1,0]:INFO:root:Epoch[133] Batch[1200] Loss[4.389] +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[1200] rmse=0.020564 lr=0.208646 +[1,0]:INFO:root:Epoch[133] Rank[0] Batch[1251] Time cost=399.61 Train-metric=0.020571 +[1,0]:INFO:root:Epoch[133] Speed: 3205.66 samples/sec +[1,0]:INFO:root:Epoch[134] Batch[100] Loss[5.255] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[100] rmse=0.020327 lr=0.208360 +[1,0]:INFO:root:Epoch[134] Batch[200] Loss[2.776] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[200] rmse=0.020426 lr=0.208171 +[1,0]:INFO:root:Epoch[134] Batch[300] Loss[2.604] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[300] rmse=0.020471 lr=0.207982 +[1,0]:INFO:root:Epoch[134] Batch[400] Loss[3.835] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[400] rmse=0.020469 lr=0.207793 +[1,0]:INFO:root:Epoch[134] Batch[500] Loss[5.063] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[500] rmse=0.020498 lr=0.207604 +[1,0]:INFO:root:Epoch[134] Batch[600] Loss[3.410] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[600] rmse=0.020496 lr=0.207414 +[1,0]:INFO:root:Epoch[134] Batch[700] Loss[2.710] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[700] rmse=0.020506 lr=0.207225 +[1,0]:INFO:root:Epoch[134] Batch[800] Loss[2.623] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[800] rmse=0.020520 lr=0.207036 +[1,0]:INFO:root:Epoch[134] Batch[900] Loss[2.856] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[900] rmse=0.020529 lr=0.206847 +[1,0]:INFO:root:Epoch[134] Batch[1000] Loss[3.929] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[1000] rmse=0.020526 lr=0.206657 +[1,0]:INFO:root:Epoch[134] Batch[1100] Loss[3.269] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[1100] rmse=0.020522 lr=0.206468 +[1,0]:INFO:root:Epoch[134] Batch[1200] Loss[4.449] +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[1200] rmse=0.020534 lr=0.206279 +[1,0]:INFO:root:Epoch[134] Rank[0] Batch[1251] Time cost=399.35 Train-metric=0.020532 +[1,0]:INFO:root:Epoch[134] Speed: 3207.73 samples/sec +[1,0]:INFO:root:Epoch[134] Rank[0] Validation-accuracy=0.633520 Validation-top_k_accuracy_5=0.855260 +[1,0]:INFO:root:Epoch[135] Batch[100] Loss[2.670] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[100] rmse=0.020461 lr=0.205993 +[1,0]:INFO:root:Epoch[135] Batch[200] Loss[2.979] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[200] rmse=0.020396 lr=0.205804 +[1,0]:INFO:root:Epoch[135] Batch[300] Loss[2.865] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[300] rmse=0.020417 lr=0.205614 +[1,0]:INFO:root:Epoch[135] Batch[400] Loss[2.918] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[400] rmse=0.020394 lr=0.205425 +[1,0]:INFO:root:Epoch[135] Batch[500] Loss[2.808] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[500] rmse=0.020397 lr=0.205236 +[1,0]:INFO:root:Epoch[135] Batch[600] Loss[2.772] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[600] rmse=0.020377 lr=0.205046 +[1,0]:INFO:root:Epoch[135] Batch[700] Loss[2.565] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[700] rmse=0.020400 lr=0.204857 +[1,0]:INFO:root:Epoch[135] Batch[800] Loss[3.879] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[800] rmse=0.020400 lr=0.204668 +[1,0]:INFO:root:Epoch[135] Batch[900] Loss[5.385] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[900] rmse=0.020425 lr=0.204478 +[1,0]:INFO:root:Epoch[135] Batch[1000] Loss[4.687] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[1000] rmse=0.020440 lr=0.204289 +[1,0]:INFO:root:Epoch[135] Batch[1100] Loss[2.855] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[1100] rmse=0.020451 lr=0.204100 +[1,0]:INFO:root:Epoch[135] Batch[1200] Loss[2.909] +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[1200] rmse=0.020472 lr=0.203910 +[1,0]:INFO:root:Epoch[135] Rank[0] Batch[1251] Time cost=399.71 Train-metric=0.020481 +[1,0]:INFO:root:Epoch[135] Speed: 3204.87 samples/sec +[1,0]:INFO:root:Epoch[136] Batch[100] Loss[3.021] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[100] rmse=0.020312 lr=0.203624 +[1,0]:INFO:root:Epoch[136] Batch[200] Loss[2.918] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[200] rmse=0.020279 lr=0.203435 +[1,0]:INFO:root:Epoch[136] Batch[300] Loss[4.671] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[300] rmse=0.020321 lr=0.203246 +[1,0]:INFO:root:Epoch[136] Batch[400] Loss[2.968] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[400] rmse=0.020411 lr=0.203056 +[1,0]:INFO:root:Epoch[136] Batch[500] Loss[2.746] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[500] rmse=0.020443 lr=0.202867 +[1,0]:INFO:root:Epoch[136] Batch[600] Loss[4.421] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[600] rmse=0.020453 lr=0.202678 +[1,0]:INFO:root:Epoch[136] Batch[700] Loss[4.731] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[700] rmse=0.020489 lr=0.202488 +[1,0]:INFO:root:Epoch[136] Batch[800] Loss[3.606] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[800] rmse=0.020497 lr=0.202299 +[1,0]:INFO:root:Epoch[136] Batch[900] Loss[5.157] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[900] rmse=0.020527 lr=0.202110 +[1,0]:INFO:root:Epoch[136] Batch[1000] Loss[5.063] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[1000] rmse=0.020532 lr=0.201920 +[1,0]:INFO:root:Epoch[136] Batch[1100] Loss[3.088] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[1100] rmse=0.020538 lr=0.201731 +[1,0]:INFO:root:Epoch[136] Batch[1200] Loss[3.298] +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[1200] rmse=0.020550 lr=0.201542 +[1,0]:INFO:root:Epoch[136] Rank[0] Batch[1251] Time cost=399.11 Train-metric=0.020562 +[1,0]:INFO:root:Epoch[136] Speed: 3209.70 samples/sec +[1,0]:INFO:root:Epoch[137] Batch[100] Loss[5.215] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[100] rmse=0.020477 lr=0.201256 +[1,0]:INFO:root:Epoch[137] Batch[200] Loss[3.150] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[200] rmse=0.020490 lr=0.201066 +[1,0]:INFO:root:Epoch[137] Batch[300] Loss[3.194] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[300] rmse=0.020554 lr=0.200877 +[1,0]:INFO:root:Epoch[137] Batch[400] Loss[3.180] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[400] rmse=0.020540 lr=0.200687 +[1,0]:INFO:root:Epoch[137] Batch[500] Loss[3.499] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[500] rmse=0.020538 lr=0.200498 +[1,0]:INFO:root:Epoch[137] Batch[600] Loss[3.063] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[600] rmse=0.020530 lr=0.200309 +[1,0]:INFO:root:Epoch[137] Batch[700] Loss[2.600] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[700] rmse=0.020517 lr=0.200119 +[1,0]:INFO:root:Epoch[137] Batch[800] Loss[3.072] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[800] rmse=0.020546 lr=0.199930 +[1,0]:INFO:root:Epoch[137] Batch[900] Loss[3.025] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[900] rmse=0.020558 lr=0.199741 +[1,0]:INFO:root:Epoch[137] Batch[1000] Loss[3.323] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[1000] rmse=0.020542 lr=0.199551 +[1,0]:INFO:root:Epoch[137] Batch[1100] Loss[4.178] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[1100] rmse=0.020534 lr=0.199362 +[1,0]:INFO:root:Epoch[137] Batch[1200] Loss[3.885] +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[1200] rmse=0.020540 lr=0.199172 +[1,0]:INFO:root:Epoch[137] Rank[0] Batch[1251] Time cost=398.92 Train-metric=0.020546 +[1,0]:INFO:root:Epoch[137] Speed: 3211.23 samples/sec +[1,0]:INFO:root:Epoch[138] Batch[100] Loss[2.632] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[100] rmse=0.020267 lr=0.198886 +[1,0]:INFO:root:Epoch[138] Batch[200] Loss[2.925] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[200] rmse=0.020418 lr=0.198697 +[1,0]:INFO:root:Epoch[138] Batch[300] Loss[4.241] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[300] rmse=0.020504 lr=0.198508 +[1,0]:INFO:root:Epoch[138] Batch[400] Loss[3.333] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[400] rmse=0.020486 lr=0.198318 +[1,0]:INFO:root:Epoch[138] Batch[500] Loss[4.565] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[500] rmse=0.020492 lr=0.198129 +[1,0]:INFO:root:Epoch[138] Batch[600] Loss[3.253] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[600] rmse=0.020487 lr=0.197940 +[1,0]:INFO:root:Epoch[138] Batch[700] Loss[3.604] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[700] rmse=0.020491 lr=0.197750 +[1,0]:INFO:root:Epoch[138] Batch[800] Loss[2.763] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[800] rmse=0.020478 lr=0.197561 +[1,0]:INFO:root:Epoch[138] Batch[900] Loss[2.710] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[900] rmse=0.020493 lr=0.197372 +[1,0]:INFO:root:Epoch[138] Batch[1000] Loss[4.049] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[1000] rmse=0.020481 lr=0.197182 +[1,0]:INFO:root:Epoch[138] Batch[1100] Loss[3.139] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[1100] rmse=0.020495 lr=0.196993 +[1,0]:INFO:root:Epoch[138] Batch[1200] Loss[5.176] +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[1200] rmse=0.020501 lr=0.196803 +[1,0]:INFO:root:Epoch[138] Rank[0] Batch[1251] Time cost=398.74 Train-metric=0.020494 +[1,0]:INFO:root:Epoch[138] Speed: 3212.66 samples/sec +[1,0]:INFO:root:Epoch[139] Batch[100] Loss[3.681] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[100] rmse=0.020201 lr=0.196518 +[1,0]:INFO:root:Epoch[139] Batch[200] Loss[2.600] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[200] rmse=0.020277 lr=0.196328 +[1,0]:INFO:root:Epoch[139] Batch[300] Loss[2.930] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[300] rmse=0.020381 lr=0.196139 +[1,0]:INFO:root:Epoch[139] Batch[400] Loss[2.912] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[400] rmse=0.020360 lr=0.195949 +[1,4]:[ip-172-31-29-212][[55333,1],4][btl_tcp.c:559:mca_btl_tcp_recv_blocking] [1,4]:recv(116) failed: Connection reset by peer (104)[1,4]: +[1,0]:INFO:root:Epoch[139] Batch[500] Loss[4.357] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[500] rmse=0.020349 lr=0.195760 +[1,0]:INFO:root:Epoch[139] Batch[600] Loss[2.826] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[600] rmse=0.020347 lr=0.195571 +[1,0]:INFO:root:Epoch[139] Batch[700] Loss[2.855] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[700] rmse=0.020355 lr=0.195381 +[1,0]:INFO:root:Epoch[139] Batch[800] Loss[2.868] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[800] rmse=0.020371 lr=0.195192 +[1,0]:INFO:root:Epoch[139] Batch[900] Loss[3.388] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[900] rmse=0.020381 lr=0.195003 +[1,0]:INFO:root:Epoch[139] Batch[1000] Loss[2.868] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[1000] rmse=0.020422 lr=0.194814 +[1,0]:INFO:root:Epoch[139] Batch[1100] Loss[3.929] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[1100] rmse=0.020428 lr=0.194624 +[1,0]:INFO:root:Epoch[139] Batch[1200] Loss[3.846] +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[1200] rmse=0.020438 lr=0.194435 +[1,0]:INFO:root:Epoch[139] Rank[0] Batch[1251] Time cost=399.53 Train-metric=0.020436 +[1,0]:INFO:root:Epoch[139] Speed: 3206.35 samples/sec +[1,0]:INFO:root:Epoch[139] Rank[0] Validation-accuracy=0.639240 Validation-top_k_accuracy_5=0.859100 +[1,0]:INFO:root:Epoch[140] Batch[100] Loss[2.889] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[100] rmse=0.020193 lr=0.194149 +[1,0]:INFO:root:Epoch[140] Batch[200] Loss[5.259] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[200] rmse=0.020281 lr=0.193960 +[1,0]:INFO:root:Epoch[140] Batch[300] Loss[2.833] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[300] rmse=0.020322 lr=0.193770 +[1,0]:INFO:root:Epoch[140] Batch[400] Loss[2.608] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[400] rmse=0.020352 lr=0.193581 +[1,0]:INFO:root:Epoch[140] Batch[500] Loss[3.658] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[500] rmse=0.020394 lr=0.193392 +[1,0]:INFO:root:Epoch[140] Batch[600] Loss[2.970] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[600] rmse=0.020395 lr=0.193203 +[1,0]:INFO:root:Epoch[140] Batch[700] Loss[4.625] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[700] rmse=0.020407 lr=0.193013 +[1,0]:INFO:root:Epoch[140] Batch[800] Loss[4.667] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[800] rmse=0.020434 lr=0.192824 +[1,0]:INFO:root:Epoch[140] Batch[900] Loss[3.544] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[900] rmse=0.020436 lr=0.192635 +[1,0]:INFO:root:Epoch[140] Batch[1000] Loss[2.840] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[1000] rmse=0.020440 lr=0.192446 +[1,0]:INFO:root:Epoch[140] Batch[1100] Loss[3.120] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[1100] rmse=0.020426 lr=0.192256 +[1,0]:INFO:root:Epoch[140] Batch[1200] Loss[2.979] +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[1200] rmse=0.020444 lr=0.192067 +[1,0]:INFO:root:Epoch[140] Rank[0] Batch[1251] Time cost=397.16 Train-metric=0.020455 +[1,0]:INFO:root:Epoch[140] Speed: 3225.42 samples/sec +[1,0]:INFO:root:Epoch[141] Batch[100] Loss[5.103] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[100] rmse=0.020342 lr=0.191781 +[1,0]:INFO:root:Epoch[141] Batch[200] Loss[2.793] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[200] rmse=0.020334 lr=0.191592 +[1,0]:INFO:root:Epoch[141] Batch[300] Loss[4.846] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[300] rmse=0.020366 lr=0.191403 +[1,0]:INFO:root:Epoch[141] Batch[400] Loss[2.586] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[400] rmse=0.020359 lr=0.191214 +[1,0]:INFO:root:Epoch[141] Batch[500] Loss[2.775] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[500] rmse=0.020385 lr=0.191025 +[1,0]:INFO:root:Epoch[141] Batch[600] Loss[4.597] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[600] rmse=0.020405 lr=0.190835 +[1,0]:INFO:root:Epoch[141] Batch[700] Loss[4.510] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[700] rmse=0.020398 lr=0.190646 +[1,0]:INFO:root:Epoch[141] Batch[800] Loss[4.167] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[800] rmse=0.020400 lr=0.190457 +[1,0]:INFO:root:Epoch[141] Batch[900] Loss[2.911] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[900] rmse=0.020405 lr=0.190268 +[1,0]:INFO:root:Epoch[141] Batch[1000] Loss[4.285] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[1000] rmse=0.020388 lr=0.190079 +[1,0]:INFO:root:Epoch[141] Batch[1100] Loss[4.014] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[1100] rmse=0.020392 lr=0.189890 +[1,0]:INFO:root:Epoch[141] Batch[1200] Loss[4.957] +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[1200] rmse=0.020400 lr=0.189700 +[1,0]:INFO:root:Epoch[141] Rank[0] Batch[1251] Time cost=399.36 Train-metric=0.020412 +[1,0]:INFO:root:Epoch[141] Speed: 3207.65 samples/sec +[1,0]:INFO:root:Epoch[142] Batch[100] Loss[2.645] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[100] rmse=0.020344 lr=0.189415 +[1,0]:INFO:root:Epoch[142] Batch[200] Loss[3.564] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[200] rmse=0.020392 lr=0.189226 +[1,0]:INFO:root:Epoch[142] Batch[300] Loss[5.010] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[300] rmse=0.020443 lr=0.189037 +[1,0]:INFO:root:Epoch[142] Batch[400] Loss[2.501] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[400] rmse=0.020423 lr=0.188848 +[1,0]:INFO:root:Epoch[142] Batch[500] Loss[3.339] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[500] rmse=0.020424 lr=0.188659 +[1,0]:INFO:root:Epoch[142] Batch[600] Loss[2.999] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[600] rmse=0.020414 lr=0.188469 +[1,0]:INFO:root:Epoch[142] Batch[700] Loss[2.715] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[700] rmse=0.020420 lr=0.188280 +[1,0]:INFO:root:Epoch[142] Batch[800] Loss[4.537] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[800] rmse=0.020437 lr=0.188091 +[1,0]:INFO:root:Epoch[142] Batch[900] Loss[2.697] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[900] rmse=0.020435 lr=0.187902 +[1,0]:INFO:root:Epoch[142] Batch[1000] Loss[4.291] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[1000] rmse=0.020435 lr=0.187713 +[1,0]:INFO:root:Epoch[142] Batch[1100] Loss[4.882] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[1100] rmse=0.020435 lr=0.187524 +[1,0]:INFO:root:Epoch[142] Batch[1200] Loss[2.440] +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[1200] rmse=0.020444 lr=0.187335 +[1,0]:INFO:root:Epoch[142] Rank[0] Batch[1251] Time cost=399.43 Train-metric=0.020452 +[1,0]:INFO:root:Epoch[142] Speed: 3207.15 samples/sec +[1,0]:INFO:root:Epoch[143] Batch[100] Loss[3.846] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[100] rmse=0.020147 lr=0.187050 +[1,0]:INFO:root:Epoch[143] Batch[200] Loss[3.235] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[200] rmse=0.020257 lr=0.186861 +[1,0]:INFO:root:Epoch[143] Batch[300] Loss[2.778] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[300] rmse=0.020342 lr=0.186672 +[1,0]:INFO:root:Epoch[143] Batch[400] Loss[2.635] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[400] rmse=0.020379 lr=0.186483 +[1,0]:INFO:root:Epoch[143] Batch[500] Loss[2.792] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[500] rmse=0.020429 lr=0.186294 +[1,0]:INFO:root:Epoch[143] Batch[600] Loss[2.742] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[600] rmse=0.020434 lr=0.186105 +[1,0]:INFO:root:Epoch[143] Batch[700] Loss[4.504] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[700] rmse=0.020429 lr=0.185916 +[1,0]:INFO:root:Epoch[143] Batch[800] Loss[2.823] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[800] rmse=0.020420 lr=0.185727 +[1,0]:INFO:root:Epoch[143] Batch[900] Loss[2.761] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[900] rmse=0.020424 lr=0.185538 +[1,0]:INFO:root:Epoch[143] Batch[1000] Loss[3.934] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[1000] rmse=0.020427 lr=0.185350 +[1,0]:INFO:root:Epoch[143] Batch[1100] Loss[2.908] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[1100] rmse=0.020430 lr=0.185161 +[1,0]:INFO:root:Epoch[143] Batch[1200] Loss[2.965] +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[1200] rmse=0.020432 lr=0.184972 +[1,0]:INFO:root:Epoch[143] Rank[0] Batch[1251] Time cost=399.64 Train-metric=0.020433 +[1,0]:INFO:root:Epoch[143] Speed: 3205.42 samples/sec +[1,0]:INFO:root:Epoch[144] Batch[100] Loss[2.627] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[100] rmse=0.020345 lr=0.184687 +[1,0]:INFO:root:Epoch[144] Batch[200] Loss[3.447] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[200] rmse=0.020390 lr=0.184498 +[1,0]:INFO:root:Epoch[144] Batch[300] Loss[2.709] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[300] rmse=0.020384 lr=0.184309 +[1,0]:INFO:root:Epoch[144] Batch[400] Loss[2.705] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[400] rmse=0.020373 lr=0.184120 +[1,0]:INFO:root:Epoch[144] Batch[500] Loss[2.979] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[500] rmse=0.020363 lr=0.183932 +[1,0]:INFO:root:Epoch[144] Batch[600] Loss[2.689] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[600] rmse=0.020352 lr=0.183743 +[1,0]:INFO:root:Epoch[144] Batch[700] Loss[3.904] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[700] rmse=0.020363 lr=0.183554 +[1,0]:INFO:root:Epoch[144] Batch[800] Loss[3.006] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[800] rmse=0.020370 lr=0.183365 +[1,0]:INFO:root:Epoch[144] Batch[900] Loss[3.342] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[900] rmse=0.020359 lr=0.183177 +[1,0]:INFO:root:Epoch[144] Batch[1000] Loss[4.887] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[1000] rmse=0.020384 lr=0.182988 +[1,0]:INFO:root:Epoch[144] Batch[1100] Loss[2.629] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[1100] rmse=0.020380 lr=0.182799 +[1,0]:INFO:root:Epoch[144] Batch[1200] Loss[4.004] +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[1200] rmse=0.020351 lr=0.182611 +[1,0]:INFO:root:Epoch[144] Rank[0] Batch[1251] Time cost=399.77 Train-metric=0.020359 +[1,0]:INFO:root:Epoch[144] Speed: 3204.37 samples/sec +[1,0]:INFO:root:Epoch[144] Rank[0] Validation-accuracy=0.647600 Validation-top_k_accuracy_5=0.863360 +[1,0]:INFO:root:Epoch[145] Batch[100] Loss[4.492] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[100] rmse=0.020272 lr=0.182326 +[1,0]:INFO:root:Epoch[145] Batch[200] Loss[5.061] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[200] rmse=0.020304 lr=0.182137 +[1,0]:INFO:root:Epoch[145] Batch[300] Loss[2.753] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[300] rmse=0.020321 lr=0.181948 +[1,0]:INFO:root:Epoch[145] Batch[400] Loss[3.133] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[400] rmse=0.020300 lr=0.181760 +[1,0]:INFO:root:Epoch[145] Batch[500] Loss[2.806] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[500] rmse=0.020321 lr=0.181571 +[1,0]:INFO:root:Epoch[145] Batch[600] Loss[2.612] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[600] rmse=0.020328 lr=0.181383 +[1,0]:INFO:root:Epoch[145] Batch[700] Loss[2.838] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[700] rmse=0.020356 lr=0.181194 +[1,0]:INFO:root:Epoch[145] Batch[800] Loss[3.753] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[800] rmse=0.020371 lr=0.181006 +[1,0]:INFO:root:Epoch[145] Batch[900] Loss[2.823] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[900] rmse=0.020377 lr=0.180817 +[1,0]:INFO:root:Epoch[145] Batch[1000] Loss[4.226] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[1000] rmse=0.020363 lr=0.180629 +[1,0]:INFO:root:Epoch[145] Batch[1100] Loss[5.143] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[1100] rmse=0.020356 lr=0.180440 +[1,0]:INFO:root:Epoch[145] Batch[1200] Loss[4.959] +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[1200] rmse=0.020355 lr=0.180252 +[1,0]:INFO:root:Epoch[145] Rank[0] Batch[1251] Time cost=398.69 Train-metric=0.020353 +[1,0]:INFO:root:Epoch[145] Speed: 3213.07 samples/sec +[1,0]:INFO:root:Epoch[146] Batch[100] Loss[2.444] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[100] rmse=0.020277 lr=0.179967 +[1,0]:INFO:root:Epoch[146] Batch[200] Loss[3.617] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[200] rmse=0.020218 lr=0.179779 +[1,0]:INFO:root:Epoch[146] Batch[300] Loss[2.994] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[300] rmse=0.020266 lr=0.179590 +[1,0]:INFO:root:Epoch[146] Batch[400] Loss[2.611] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[400] rmse=0.020281 lr=0.179402 +[1,0]:INFO:root:Epoch[146] Batch[500] Loss[3.146] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[500] rmse=0.020354 lr=0.179214 +[1,0]:INFO:root:Epoch[146] Batch[600] Loss[4.415] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[600] rmse=0.020317 lr=0.179025 +[1,0]:INFO:root:Epoch[146] Batch[700] Loss[2.584] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[700] rmse=0.020315 lr=0.178837 +[1,0]:INFO:root:Epoch[146] Batch[800] Loss[2.799] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[800] rmse=0.020303 lr=0.178649 +[1,0]:INFO:root:Epoch[146] Batch[900] Loss[2.663] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[900] rmse=0.020329 lr=0.178460 +[1,0]:INFO:root:Epoch[146] Batch[1000] Loss[2.642] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[1000] rmse=0.020328 lr=0.178272 +[1,0]:INFO:root:Epoch[146] Batch[1100] Loss[2.790] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[1100] rmse=0.020340 lr=0.178084 +[1,0]:INFO:root:Epoch[146] Batch[1200] Loss[2.553] +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[1200] rmse=0.020353 lr=0.177896 +[1,0]:INFO:root:Epoch[146] Rank[0] Batch[1251] Time cost=398.84 Train-metric=0.020360 +[1,0]:INFO:root:Epoch[146] Speed: 3211.91 samples/sec +[1,0]:INFO:root:Epoch[147] Batch[100] Loss[2.677] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[100] rmse=0.020142 lr=0.177611 +[1,0]:INFO:root:Epoch[147] Batch[200] Loss[4.892] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[200] rmse=0.020156 lr=0.177423 +[1,0]:INFO:root:Epoch[147] Batch[300] Loss[5.189] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[300] rmse=0.020248 lr=0.177235 +[1,0]:INFO:root:Epoch[147] Batch[400] Loss[2.791] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[400] rmse=0.020282 lr=0.177047 +[1,0]:INFO:root:Epoch[147] Batch[500] Loss[2.705] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[500] rmse=0.020309 lr=0.176859 +[1,0]:INFO:root:Epoch[147] Batch[600] Loss[3.816] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[600] rmse=0.020296 lr=0.176671 +[1,0]:INFO:root:Epoch[147] Batch[700] Loss[2.620] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[700] rmse=0.020310 lr=0.176483 +[1,0]:INFO:root:Epoch[147] Batch[800] Loss[3.965] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[800] rmse=0.020304 lr=0.176295 +[1,0]:INFO:root:Epoch[147] Batch[900] Loss[4.286] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[900] rmse=0.020294 lr=0.176107 +[1,0]:INFO:root:Epoch[147] Batch[1000] Loss[3.728] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[1000] rmse=0.020293 lr=0.175919 +[1,0]:INFO:root:Epoch[147] Batch[1100] Loss[3.108] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[1100] rmse=0.020298 lr=0.175731 +[1,0]:INFO:root:Epoch[147] Batch[1200] Loss[3.138] +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[1200] rmse=0.020309 lr=0.175543 +[1,0]:INFO:root:Epoch[147] Rank[0] Batch[1251] Time cost=404.35 Train-metric=0.020319 +[1,0]:INFO:root:Epoch[147] Speed: 3168.12 samples/sec +[1,0]:INFO:root:Epoch[148] Batch[100] Loss[4.380] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[100] rmse=0.020142 lr=0.175259 +[1,0]:INFO:root:Epoch[148] Batch[200] Loss[3.245] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[200] rmse=0.020235 lr=0.175071 +[1,0]:INFO:root:Epoch[148] Batch[300] Loss[2.649] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[300] rmse=0.020277 lr=0.174883 +[1,0]:INFO:root:Epoch[148] Batch[400] Loss[2.739] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[400] rmse=0.020258 lr=0.174695 +[1,0]:INFO:root:Epoch[148] Batch[500] Loss[2.924] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[500] rmse=0.020248 lr=0.174507 +[1,0]:INFO:root:Epoch[148] Batch[600] Loss[2.567] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[600] rmse=0.020286 lr=0.174319 +[1,0]:INFO:root:Epoch[148] Batch[700] Loss[2.915] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[700] rmse=0.020305 lr=0.174132 +[1,0]:INFO:root:Epoch[148] Batch[800] Loss[2.830] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[800] rmse=0.020298 lr=0.173944 +[1,0]:INFO:root:Epoch[148] Batch[900] Loss[2.903] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[900] rmse=0.020299 lr=0.173756 +[1,0]:INFO:root:Epoch[148] Batch[1000] Loss[5.075] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[1000] rmse=0.020307 lr=0.173568 +[1,0]:INFO:root:Epoch[148] Batch[1100] Loss[3.012] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[1100] rmse=0.020325 lr=0.173381 +[1,0]:INFO:root:Epoch[148] Batch[1200] Loss[4.857] +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[1200] rmse=0.020332 lr=0.173193 +[1,0]:INFO:root:Epoch[148] Rank[0] Batch[1251] Time cost=401.04 Train-metric=0.020343 +[1,0]:INFO:root:Epoch[148] Speed: 3194.26 samples/sec +[1,0]:INFO:root:Epoch[149] Batch[100] Loss[2.498] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[100] rmse=0.020209 lr=0.172910 +[1,0]:INFO:root:Epoch[149] Batch[200] Loss[4.700] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[200] rmse=0.020240 lr=0.172722 +[1,0]:INFO:root:Epoch[149] Batch[300] Loss[3.654] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[300] rmse=0.020230 lr=0.172534 +[1,0]:INFO:root:Epoch[149] Batch[400] Loss[2.784] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[400] rmse=0.020211 lr=0.172347 +[1,0]:INFO:root:Epoch[149] Batch[500] Loss[5.228] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[500] rmse=0.020222 lr=0.172159 +[1,0]:INFO:root:Epoch[149] Batch[600] Loss[2.619] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[600] rmse=0.020225 lr=0.171972 +[1,0]:INFO:root:Epoch[149] Batch[700] Loss[2.656] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[700] rmse=0.020249 lr=0.171784 +[1,0]:INFO:root:Epoch[149] Batch[800] Loss[4.053] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[800] rmse=0.020284 lr=0.171597 +[1,0]:INFO:root:Epoch[149] Batch[900] Loss[4.806] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[900] rmse=0.020303 lr=0.171409 +[1,0]:INFO:root:Epoch[149] Batch[1000] Loss[3.109] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[1000] rmse=0.020323 lr=0.171222 +[1,0]:INFO:root:Epoch[149] Batch[1100] Loss[4.427] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[1100] rmse=0.020337 lr=0.171035 +[1,0]:INFO:root:Epoch[149] Batch[1200] Loss[3.086] +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[1200] rmse=0.020332 lr=0.170847 +[1,0]:INFO:root:Epoch[149] Rank[0] Batch[1251] Time cost=402.03 Train-metric=0.020327 +[1,0]:INFO:root:Epoch[149] Speed: 3186.40 samples/sec +[1,0]:INFO:root:Epoch[149] Rank[0] Validation-accuracy=0.648860 Validation-top_k_accuracy_5=0.866020 +[1,0]:INFO:root:Epoch[150] Batch[100] Loss[3.380] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[100] rmse=0.019989 lr=0.170564 +[1,0]:INFO:root:Epoch[150] Batch[200] Loss[2.980] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[200] rmse=0.020178 lr=0.170377 +[1,0]:INFO:root:Epoch[150] Batch[300] Loss[4.684] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[300] rmse=0.020166 lr=0.170190 +[1,0]:INFO:root:Epoch[150] Batch[400] Loss[2.772] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[400] rmse=0.020202 lr=0.170003 +[1,0]:INFO:root:Epoch[150] Batch[500] Loss[3.681] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[500] rmse=0.020268 lr=0.169815 +[1,0]:INFO:root:Epoch[150] Batch[600] Loss[4.110] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[600] rmse=0.020271 lr=0.169628 +[1,0]:INFO:root:Epoch[150] Batch[700] Loss[2.985] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[700] rmse=0.020273 lr=0.169441 +[1,0]:INFO:root:Epoch[150] Batch[800] Loss[3.607] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[800] rmse=0.020302 lr=0.169254 +[1,0]:INFO:root:Epoch[150] Batch[900] Loss[5.175] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[900] rmse=0.020315 lr=0.169067 +[1,0]:INFO:root:Epoch[150] Batch[1000] Loss[2.833] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[1000] rmse=0.020312 lr=0.168880 +[1,0]:INFO:root:Epoch[150] Batch[1100] Loss[3.437] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[1100] rmse=0.020318 lr=0.168693 +[1,0]:INFO:root:Epoch[150] Batch[1200] Loss[2.461] +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[1200] rmse=0.020323 lr=0.168506 +[1,0]:INFO:root:Epoch[150] Rank[0] Batch[1251] Time cost=401.40 Train-metric=0.020331 +[1,0]:INFO:root:Epoch[150] Speed: 3191.40 samples/sec +[1,0]:INFO:root:Epoch[151] Batch[100] Loss[4.970] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[100] rmse=0.020214 lr=0.168223 +[1,0]:INFO:root:Epoch[151] Batch[200] Loss[4.643] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[200] rmse=0.020201 lr=0.168036 +[1,0]:INFO:root:Epoch[151] Batch[300] Loss[5.151] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[300] rmse=0.020212 lr=0.167849 +[1,0]:INFO:root:Epoch[151] Batch[400] Loss[3.576] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[400] rmse=0.020269 lr=0.167662 +[1,0]:INFO:root:Epoch[151] Batch[500] Loss[2.898] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[500] rmse=0.020284 lr=0.167475 +[1,0]:INFO:root:Epoch[151] Batch[600] Loss[2.742] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[600] rmse=0.020285 lr=0.167289 +[1,0]:INFO:root:Epoch[151] Batch[700] Loss[5.054] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[700] rmse=0.020308 lr=0.167102 +[1,0]:INFO:root:Epoch[151] Batch[800] Loss[2.883] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[800] rmse=0.020311 lr=0.166915 +[1,0]:INFO:root:Epoch[151] Batch[900] Loss[4.283] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[900] rmse=0.020324 lr=0.166728 +[1,0]:INFO:root:Epoch[151] Batch[1000] Loss[4.464] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[1000] rmse=0.020329 lr=0.166542 +[1,0]:INFO:root:Epoch[151] Batch[1100] Loss[2.727] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[1100] rmse=0.020341 lr=0.166355 +[1,0]:INFO:root:Epoch[151] Batch[1200] Loss[2.607] +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[1200] rmse=0.020330 lr=0.166168 +[1,0]:INFO:root:Epoch[151] Rank[0] Batch[1251] Time cost=399.24 Train-metric=0.020335 +[1,0]:INFO:root:Epoch[151] Speed: 3208.66 samples/sec +[1,0]:INFO:root:Epoch[152] Batch[100] Loss[4.715] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[100] rmse=0.020245 lr=0.165886 +[1,0]:INFO:root:Epoch[152] Batch[200] Loss[3.175] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[200] rmse=0.020204 lr=0.165700 +[1,0]:INFO:root:Epoch[152] Batch[300] Loss[2.904] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[300] rmse=0.020204 lr=0.165513 +[1,0]:INFO:root:Epoch[152] Batch[400] Loss[2.510] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[400] rmse=0.020231 lr=0.165327 +[1,0]:INFO:root:Epoch[152] Batch[500] Loss[3.408] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[500] rmse=0.020241 lr=0.165140 +[1,0]:INFO:root:Epoch[152] Batch[600] Loss[4.702] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[600] rmse=0.020215 lr=0.164954 +[1,0]:INFO:root:Epoch[152] Batch[700] Loss[2.784] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[700] rmse=0.020230 lr=0.164767 +[1,0]:INFO:root:Epoch[152] Batch[800] Loss[2.555] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[800] rmse=0.020250 lr=0.164581 +[1,0]:INFO:root:Epoch[152] Batch[900] Loss[3.142] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[900] rmse=0.020240 lr=0.164395 +[1,0]:INFO:root:Epoch[152] Batch[1000] Loss[2.596] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[1000] rmse=0.020240 lr=0.164208 +[1,0]:INFO:root:Epoch[152] Batch[1100] Loss[3.213] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[1100] rmse=0.020240 lr=0.164022 +[1,0]:INFO:root:Epoch[152] Batch[1200] Loss[2.945] +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[1200] rmse=0.020240 lr=0.163836 +[1,0]:INFO:root:Epoch[152] Rank[0] Batch[1251] Time cost=398.98 Train-metric=0.020236 +[1,0]:INFO:root:Epoch[152] Speed: 3210.73 samples/sec +[1,0]:INFO:root:Epoch[153] Batch[100] Loss[4.846] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[100] rmse=0.020242 lr=0.163554 +[1,0]:INFO:root:Epoch[153] Batch[200] Loss[2.611] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[200] rmse=0.020179 lr=0.163368 +[1,0]:INFO:root:Epoch[153] Batch[300] Loss[3.374] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[300] rmse=0.020206 lr=0.163182 +[1,0]:INFO:root:Epoch[153] Batch[400] Loss[3.784] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[400] rmse=0.020180 lr=0.162996 +[1,0]:INFO:root:Epoch[153] Batch[500] Loss[5.000] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[500] rmse=0.020181 lr=0.162810 +[1,0]:INFO:root:Epoch[153] Batch[600] Loss[3.536] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[600] rmse=0.020179 lr=0.162624 +[1,0]:INFO:root:Epoch[153] Batch[700] Loss[3.961] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[700] rmse=0.020173 lr=0.162438 +[1,0]:INFO:root:Epoch[153] Batch[800] Loss[2.787] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[800] rmse=0.020191 lr=0.162252 +[1,0]:INFO:root:Epoch[153] Batch[900] Loss[2.754] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[900] rmse=0.020214 lr=0.162066 +[1,0]:INFO:root:Epoch[153] Batch[1000] Loss[5.287] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[1000] rmse=0.020234 lr=0.161880 +[1,0]:INFO:root:Epoch[153] Batch[1100] Loss[4.343] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[1100] rmse=0.020245 lr=0.161694 +[1,0]:INFO:root:Epoch[153] Batch[1200] Loss[4.877] +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[1200] rmse=0.020252 lr=0.161508 +[1,0]:INFO:root:Epoch[153] Rank[0] Batch[1251] Time cost=399.32 Train-metric=0.020254 +[1,0]:INFO:root:Epoch[153] Speed: 3208.00 samples/sec +[1,0]:INFO:root:Epoch[154] Batch[100] Loss[3.421] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[100] rmse=0.020001 lr=0.161228 +[1,0]:INFO:root:Epoch[154] Batch[200] Loss[2.706] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[200] rmse=0.020203 lr=0.161042 +[1,0]:INFO:root:Epoch[154] Batch[300] Loss[2.606] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[300] rmse=0.020189 lr=0.160856 +[1,0]:INFO:root:Epoch[154] Batch[400] Loss[5.021] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[400] rmse=0.020212 lr=0.160670 +[1,0]:INFO:root:Epoch[154] Batch[500] Loss[4.257] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[500] rmse=0.020177 lr=0.160485 +[1,0]:INFO:root:Epoch[154] Batch[600] Loss[4.493] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[600] rmse=0.020207 lr=0.160299 +[1,0]:INFO:root:Epoch[154] Batch[700] Loss[2.588] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[700] rmse=0.020204 lr=0.160114 +[1,0]:INFO:root:Epoch[154] Batch[800] Loss[2.770] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[800] rmse=0.020205 lr=0.159928 +[1,0]:INFO:root:Epoch[154] Batch[900] Loss[4.775] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[900] rmse=0.020226 lr=0.159742 +[1,0]:INFO:root:Epoch[154] Batch[1000] Loss[2.707] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[1000] rmse=0.020230 lr=0.159557 +[1,0]:INFO:root:Epoch[154] Batch[1100] Loss[4.969] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[1100] rmse=0.020265 lr=0.159372 +[1,0]:INFO:root:Epoch[154] Batch[1200] Loss[2.751] +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[1200] rmse=0.020283 lr=0.159186 +[1,0]:INFO:root:Epoch[154] Rank[0] Batch[1251] Time cost=399.33 Train-metric=0.020274 +[1,0]:INFO:root:Epoch[154] Speed: 3207.91 samples/sec +[1,0]:INFO:root:Epoch[154] Rank[0] Validation-accuracy=0.647400 Validation-top_k_accuracy_5=0.865260 +[1,0]:INFO:root:Epoch[155] Batch[100] Loss[2.531] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[100] rmse=0.020182 lr=0.158906 +[1,0]:INFO:root:Epoch[155] Batch[200] Loss[2.765] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[200] rmse=0.020178 lr=0.158721 +[1,0]:INFO:root:Epoch[155] Batch[300] Loss[4.566] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[300] rmse=0.020177 lr=0.158536 +[1,0]:INFO:root:Epoch[155] Batch[400] Loss[2.799] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[400] rmse=0.020167 lr=0.158350 +[1,0]:INFO:root:Epoch[155] Batch[500] Loss[4.911] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[500] rmse=0.020195 lr=0.158165 +[1,0]:INFO:root:Epoch[155] Batch[600] Loss[3.744] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[600] rmse=0.020146 lr=0.157980 +[1,0]:INFO:root:Epoch[155] Batch[700] Loss[4.707] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[700] rmse=0.020162 lr=0.157795 +[1,0]:INFO:root:Epoch[155] Batch[800] Loss[4.942] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[800] rmse=0.020188 lr=0.157610 +[1,0]:INFO:root:Epoch[155] Batch[900] Loss[2.615] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[900] rmse=0.020182 lr=0.157425 +[1,0]:INFO:root:Epoch[155] Batch[1000] Loss[2.935] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[1000] rmse=0.020201 lr=0.157240 +[1,0]:INFO:root:Epoch[155] Batch[1100] Loss[2.857] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[1100] rmse=0.020217 lr=0.157055 +[1,0]:INFO:root:Epoch[155] Batch[1200] Loss[4.613] +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[1200] rmse=0.020218 lr=0.156870 +[1,0]:INFO:root:Epoch[155] Rank[0] Batch[1251] Time cost=398.96 Train-metric=0.020229 +[1,0]:INFO:root:Epoch[155] Speed: 3210.94 samples/sec +[1,0]:INFO:root:Epoch[156] Batch[100] Loss[2.830] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[100] rmse=0.020041 lr=0.156591 +[1,0]:INFO:root:Epoch[156] Batch[200] Loss[2.871] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[200] rmse=0.020121 lr=0.156406 +[1,0]:INFO:root:Epoch[156] Batch[300] Loss[2.748] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[300] rmse=0.020118 lr=0.156221 +[1,0]:INFO:root:Epoch[156] Batch[400] Loss[2.543] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[400] rmse=0.020134 lr=0.156036 +[1,0]:INFO:root:Epoch[156] Batch[500] Loss[3.118] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[500] rmse=0.020131 lr=0.155851 +[1,0]:INFO:root:Epoch[156] Batch[600] Loss[4.967] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[600] rmse=0.020155 lr=0.155667 +[1,0]:INFO:root:Epoch[156] Batch[700] Loss[2.584] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[700] rmse=0.020166 lr=0.155482 +[1,0]:INFO:root:Epoch[156] Batch[800] Loss[2.789] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[800] rmse=0.020146 lr=0.155297 +[1,0]:INFO:root:Epoch[156] Batch[900] Loss[3.797] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[900] rmse=0.020151 lr=0.155113 +[1,0]:INFO:root:Epoch[156] Batch[1000] Loss[2.791] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[1000] rmse=0.020164 lr=0.154928 +[1,0]:INFO:root:Epoch[156] Batch[1100] Loss[3.248] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[1100] rmse=0.020176 lr=0.154744 +[1,0]:INFO:root:Epoch[156] Batch[1200] Loss[3.028] +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[1200] rmse=0.020178 lr=0.154559 +[1,0]:INFO:root:Epoch[156] Rank[0] Batch[1251] Time cost=399.17 Train-metric=0.020187 +[1,0]:INFO:root:Epoch[156] Speed: 3209.22 samples/sec +[1,0]:INFO:root:Epoch[157] Batch[100] Loss[2.764] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[100] rmse=0.020223 lr=0.154281 +[1,0]:INFO:root:Epoch[157] Batch[200] Loss[3.041] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[200] rmse=0.020185 lr=0.154097 +[1,0]:INFO:root:Epoch[157] Batch[300] Loss[2.458] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[300] rmse=0.020159 lr=0.153912 +[1,0]:INFO:root:Epoch[157] Batch[400] Loss[3.169] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[400] rmse=0.020168 lr=0.153728 +[1,0]:INFO:root:Epoch[157] Batch[500] Loss[4.152] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[500] rmse=0.020184 lr=0.153544 +[1,0]:INFO:root:Epoch[157] Batch[600] Loss[2.871] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[600] rmse=0.020166 lr=0.153360 +[1,0]:INFO:root:Epoch[157] Batch[700] Loss[2.798] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[700] rmse=0.020160 lr=0.153176 +[1,0]:INFO:root:Epoch[157] Batch[800] Loss[2.650] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[800] rmse=0.020161 lr=0.152991 +[1,0]:INFO:root:Epoch[157] Batch[900] Loss[2.466] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[900] rmse=0.020169 lr=0.152807 +[1,0]:INFO:root:Epoch[157] Batch[1000] Loss[2.941] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[1000] rmse=0.020183 lr=0.152623 +[1,0]:INFO:root:Epoch[157] Batch[1100] Loss[2.752] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[1100] rmse=0.020177 lr=0.152439 +[1,0]:INFO:root:Epoch[157] Batch[1200] Loss[2.735] +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[1200] rmse=0.020174 lr=0.152256 +[1,0]:INFO:root:Epoch[157] Rank[0] Batch[1251] Time cost=400.26 Train-metric=0.020179 +[1,0]:INFO:root:Epoch[157] Speed: 3200.52 samples/sec +[1,0]:INFO:root:Epoch[158] Batch[100] Loss[4.900] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[100] rmse=0.020045 lr=0.151978 +[1,0]:INFO:root:Epoch[158] Batch[200] Loss[4.489] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[200] rmse=0.020108 lr=0.151794 +[1,0]:INFO:root:Epoch[158] Batch[300] Loss[2.704] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[300] rmse=0.020148 lr=0.151610 +[1,0]:INFO:root:Epoch[158] Batch[400] Loss[3.159] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[400] rmse=0.020101 lr=0.151427 +[1,0]:INFO:root:Epoch[158] Batch[500] Loss[4.598] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[500] rmse=0.020079 lr=0.151243 +[1,0]:INFO:root:Epoch[158] Batch[600] Loss[2.579] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[600] rmse=0.020089 lr=0.151059 +[1,0]:INFO:root:Epoch[158] Batch[700] Loss[2.494] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[700] rmse=0.020096 lr=0.150876 +[1,0]:INFO:root:Epoch[158] Batch[800] Loss[3.339] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[800] rmse=0.020093 lr=0.150692 +[1,0]:INFO:root:Epoch[158] Batch[900] Loss[2.812] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[900] rmse=0.020103 lr=0.150509 +[1,0]:INFO:root:Epoch[158] Batch[1000] Loss[2.648] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[1000] rmse=0.020102 lr=0.150325 +[1,0]:INFO:root:Epoch[158] Batch[1100] Loss[2.586] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[1100] rmse=0.020120 lr=0.150142 +[1,0]:INFO:root:Epoch[158] Batch[1200] Loss[2.886] +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[1200] rmse=0.020133 lr=0.149958 +[1,0]:INFO:root:Epoch[158] Rank[0] Batch[1251] Time cost=400.20 Train-metric=0.020140 +[1,0]:INFO:root:Epoch[158] Speed: 3200.92 samples/sec +[1,0]:INFO:root:Epoch[159] Batch[100] Loss[3.097] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[100] rmse=0.020010 lr=0.149682 +[1,0]:INFO:root:Epoch[159] Batch[200] Loss[2.519] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[200] rmse=0.020051 lr=0.149498 +[1,0]:INFO:root:Epoch[159] Batch[300] Loss[2.713] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[300] rmse=0.020108 lr=0.149315 +[1,0]:INFO:root:Epoch[159] Batch[400] Loss[3.084] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[400] rmse=0.020080 lr=0.149132 +[1,0]:INFO:root:Epoch[159] Batch[500] Loss[2.517] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[500] rmse=0.020106 lr=0.148949 +[1,0]:INFO:root:Epoch[159] Batch[600] Loss[2.895] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[600] rmse=0.020095 lr=0.148766 +[1,0]:INFO:root:Epoch[159] Batch[700] Loss[4.423] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[700] rmse=0.020100 lr=0.148583 +[1,0]:INFO:root:Epoch[159] Batch[800] Loss[3.050] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[800] rmse=0.020108 lr=0.148400 +[1,0]:INFO:root:Epoch[159] Batch[900] Loss[2.825] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[900] rmse=0.020124 lr=0.148217 +[1,0]:INFO:root:Epoch[159] Batch[1000] Loss[4.368] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[1000] rmse=0.020116 lr=0.148034 +[1,0]:INFO:root:Epoch[159] Batch[1100] Loss[2.845] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[1100] rmse=0.020123 lr=0.147851 +[1,0]:INFO:root:Epoch[159] Batch[1200] Loss[2.756] +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[1200] rmse=0.020126 lr=0.147668 +[1,0]:INFO:root:Epoch[159] Rank[0] Batch[1251] Time cost=398.98 Train-metric=0.020131 +[1,0]:INFO:root:Epoch[159] Speed: 3210.72 samples/sec +[1,0]:INFO:root:Epoch[159] Rank[0] Validation-accuracy=0.653660 Validation-top_k_accuracy_5=0.870760 +[1,0]:INFO:root:Epoch[160] Batch[100] Loss[5.206] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[100] rmse=0.020133 lr=0.147392 +[1,0]:INFO:root:Epoch[160] Batch[200] Loss[2.722] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[200] rmse=0.020021 lr=0.147209 +[1,0]:INFO:root:Epoch[160] Batch[300] Loss[2.637] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[300] rmse=0.020028 lr=0.147027 +[1,0]:INFO:root:Epoch[160] Batch[400] Loss[2.926] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[400] rmse=0.020039 lr=0.146844 +[1,0]:INFO:root:Epoch[160] Batch[500] Loss[2.895] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[500] rmse=0.020050 lr=0.146662 +[1,0]:INFO:root:Epoch[160] Batch[600] Loss[4.385] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[600] rmse=0.020053 lr=0.146479 +[1,0]:INFO:root:Epoch[160] Batch[700] Loss[5.230] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[700] rmse=0.020078 lr=0.146297 +[1,0]:INFO:root:Epoch[160] Batch[800] Loss[2.920] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[800] rmse=0.020109 lr=0.146114 +[1,0]:INFO:root:Epoch[160] Batch[900] Loss[2.813] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[900] rmse=0.020128 lr=0.145932 +[1,0]:INFO:root:Epoch[160] Batch[1000] Loss[2.538] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[1000] rmse=0.020160 lr=0.145750 +[1,0]:INFO:root:Epoch[160] Batch[1100] Loss[3.816] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[1100] rmse=0.020159 lr=0.145567 +[1,0]:INFO:root:Epoch[160] Batch[1200] Loss[3.140] +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[1200] rmse=0.020171 lr=0.145385 +[1,0]:INFO:root:Epoch[160] Rank[0] Batch[1251] Time cost=397.75 Train-metric=0.020178 +[1,0]:INFO:root:Epoch[160] Speed: 3220.65 samples/sec +[1,0]:INFO:root:Epoch[161] Batch[100] Loss[2.658] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[100] rmse=0.020097 lr=0.145110 +[1,0]:INFO:root:Epoch[161] Batch[200] Loss[2.916] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[200] rmse=0.020108 lr=0.144928 +[1,0]:INFO:root:Epoch[161] Batch[300] Loss[4.910] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[300] rmse=0.020080 lr=0.144746 +[1,0]:INFO:root:Epoch[161] Batch[400] Loss[3.146] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[400] rmse=0.020079 lr=0.144564 +[1,0]:INFO:root:Epoch[161] Batch[500] Loss[4.639] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[500] rmse=0.020101 lr=0.144382 +[1,0]:INFO:root:Epoch[161] Batch[600] Loss[3.110] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[600] rmse=0.020111 lr=0.144200 +[1,0]:INFO:root:Epoch[161] Batch[700] Loss[4.997] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[700] rmse=0.020096 lr=0.144018 +[1,0]:INFO:root:Epoch[161] Batch[800] Loss[2.776] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[800] rmse=0.020076 lr=0.143837 +[1,0]:INFO:root:Epoch[161] Batch[900] Loss[2.884] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[900] rmse=0.020096 lr=0.143655 +[1,0]:INFO:root:Epoch[161] Batch[1000] Loss[2.809] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[1000] rmse=0.020105 lr=0.143473 +[1,0]:INFO:root:Epoch[161] Batch[1100] Loss[2.484] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[1100] rmse=0.020108 lr=0.143292 +[1,0]:INFO:root:Epoch[161] Batch[1200] Loss[5.201] +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[1200] rmse=0.020116 lr=0.143110 +[1,0]:INFO:root:Epoch[161] Rank[0] Batch[1251] Time cost=399.43 Train-metric=0.020115 +[1,0]:INFO:root:Epoch[161] Speed: 3207.13 samples/sec +[1,0]:INFO:root:Epoch[162] Batch[100] Loss[3.604] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[100] rmse=0.020027 lr=0.142836 +[1,0]:INFO:root:Epoch[162] Batch[200] Loss[4.960] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[200] rmse=0.019963 lr=0.142655 +[1,0]:INFO:root:Epoch[162] Batch[300] Loss[2.786] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[300] rmse=0.019980 lr=0.142473 +[1,0]:INFO:root:Epoch[162] Batch[400] Loss[3.019] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[400] rmse=0.019966 lr=0.142292 +[1,0]:INFO:root:Epoch[162] Batch[500] Loss[2.480] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[500] rmse=0.020010 lr=0.142110 +[1,0]:INFO:root:Epoch[162] Batch[600] Loss[2.714] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[600] rmse=0.019992 lr=0.141929 +[1,0]:INFO:root:Epoch[162] Batch[700] Loss[4.838] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[700] rmse=0.019961 lr=0.141748 +[1,0]:INFO:root:Epoch[162] Batch[800] Loss[2.544] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[800] rmse=0.019962 lr=0.141567 +[1,0]:INFO:root:Epoch[162] Batch[900] Loss[2.996] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[900] rmse=0.020004 lr=0.141386 +[1,0]:INFO:root:Epoch[162] Batch[1000] Loss[3.081] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[1000] rmse=0.020010 lr=0.141205 +[1,0]:INFO:root:Epoch[162] Batch[1100] Loss[2.542] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[1100] rmse=0.020021 lr=0.141024 +[1,0]:INFO:root:Epoch[162] Batch[1200] Loss[2.802] +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[1200] rmse=0.020044 lr=0.140843 +[1,0]:INFO:root:Epoch[162] Rank[0] Batch[1251] Time cost=398.89 Train-metric=0.020049 +[1,0]:INFO:root:Epoch[162] Speed: 3211.51 samples/sec +[1,0]:INFO:root:Epoch[163] Batch[100] Loss[2.805] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[100] rmse=0.019920 lr=0.140570 +[1,0]:INFO:root:Epoch[163] Batch[200] Loss[2.693] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[200] rmse=0.019875 lr=0.140389 +[1,0]:INFO:root:Epoch[163] Batch[300] Loss[2.679] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[300] rmse=0.019882 lr=0.140208 +[1,0]:INFO:root:Epoch[163] Batch[400] Loss[2.899] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[400] rmse=0.019939 lr=0.140028 +[1,0]:INFO:root:Epoch[163] Batch[500] Loss[3.141] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[500] rmse=0.019960 lr=0.139847 +[1,0]:INFO:root:Epoch[163] Batch[600] Loss[4.366] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[600] rmse=0.019968 lr=0.139666 +[1,0]:INFO:root:Epoch[163] Batch[700] Loss[2.704] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[700] rmse=0.019983 lr=0.139486 +[1,0]:INFO:root:Epoch[163] Batch[800] Loss[2.648] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[800] rmse=0.020015 lr=0.139305 +[1,0]:INFO:root:Epoch[163] Batch[900] Loss[4.365] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[900] rmse=0.020022 lr=0.139125 +[1,0]:INFO:root:Epoch[163] Batch[1000] Loss[2.640] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[1000] rmse=0.020033 lr=0.138945 +[1,0]:INFO:root:Epoch[163] Batch[1100] Loss[4.444] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[1100] rmse=0.020058 lr=0.138764 +[1,0]:INFO:root:Epoch[163] Batch[1200] Loss[3.987] +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[1200] rmse=0.020069 lr=0.138584 +[1,0]:INFO:root:Epoch[163] Rank[0] Batch[1251] Time cost=399.32 Train-metric=0.020068 +[1,0]:INFO:root:Epoch[163] Speed: 3208.00 samples/sec +[1,0]:INFO:root:Epoch[164] Batch[100] Loss[3.053] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[100] rmse=0.019857 lr=0.138312 +[1,0]:INFO:root:Epoch[164] Batch[200] Loss[2.551] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[200] rmse=0.019955 lr=0.138132 +[1,0]:INFO:root:Epoch[164] Batch[300] Loss[2.778] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[300] rmse=0.019992 lr=0.137952 +[1,0]:INFO:root:Epoch[164] Batch[400] Loss[3.667] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[400] rmse=0.020021 lr=0.137772 +[1,0]:INFO:root:Epoch[164] Batch[500] Loss[5.164] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[500] rmse=0.020007 lr=0.137592 +[1,0]:INFO:root:Epoch[164] Batch[600] Loss[4.637] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[600] rmse=0.020040 lr=0.137412 +[1,0]:INFO:root:Epoch[164] Batch[700] Loss[2.486] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[700] rmse=0.020052 lr=0.137232 +[1,0]:INFO:root:Epoch[164] Batch[800] Loss[4.439] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[800] rmse=0.020049 lr=0.137052 +[1,0]:INFO:root:Epoch[164] Batch[900] Loss[2.562] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[900] rmse=0.020044 lr=0.136873 +[1,0]:INFO:root:Epoch[164] Batch[1000] Loss[3.832] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[1000] rmse=0.020043 lr=0.136693 +[1,0]:INFO:root:Epoch[164] Batch[1100] Loss[2.520] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[1100] rmse=0.020043 lr=0.136513 +[1,0]:INFO:root:Epoch[164] Batch[1200] Loss[2.528] +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[1200] rmse=0.020064 lr=0.136334 +[1,0]:INFO:root:Epoch[164] Rank[0] Batch[1251] Time cost=399.21 Train-metric=0.020063 +[1,0]:INFO:root:Epoch[164] Speed: 3208.91 samples/sec +[1,0]:INFO:root:Epoch[164] Rank[0] Validation-accuracy=0.666320 Validation-top_k_accuracy_5=0.876800 +[1,0]:INFO:root:Epoch[165] Batch[100] Loss[2.770] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[100] rmse=0.020084 lr=0.136063 +[1,0]:INFO:root:Epoch[165] Batch[200] Loss[2.843] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[200] rmse=0.020120 lr=0.135883 +[1,0]:INFO:root:Epoch[165] Batch[300] Loss[4.839] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[300] rmse=0.020024 lr=0.135704 +[1,0]:INFO:root:Epoch[165] Batch[400] Loss[2.667] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[400] rmse=0.020020 lr=0.135525 +[1,0]:INFO:root:Epoch[165] Batch[500] Loss[2.839] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[500] rmse=0.020038 lr=0.135345 +[1,0]:INFO:root:Epoch[165] Batch[600] Loss[2.691] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[600] rmse=0.020049 lr=0.135166 +[1,0]:INFO:root:Epoch[165] Batch[700] Loss[4.706] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[700] rmse=0.020083 lr=0.134987 +[1,0]:INFO:root:Epoch[165] Batch[800] Loss[2.962] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[800] rmse=0.020082 lr=0.134808 +[1,0]:INFO:root:Epoch[165] Batch[900] Loss[2.756] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[900] rmse=0.020063 lr=0.134629 +[1,0]:INFO:root:Epoch[165] Batch[1000] Loss[2.771] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[1000] rmse=0.020064 lr=0.134450 +[1,0]:INFO:root:Epoch[165] Batch[1100] Loss[3.368] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[1100] rmse=0.020059 lr=0.134271 +[1,0]:INFO:root:Epoch[165] Batch[1200] Loss[3.129] +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[1200] rmse=0.020062 lr=0.134092 +[1,0]:INFO:root:Epoch[165] Rank[0] Batch[1251] Time cost=398.86 Train-metric=0.020067 +[1,0]:INFO:root:Epoch[165] Speed: 3211.72 samples/sec +[1,0]:INFO:root:Epoch[166] Batch[100] Loss[2.910] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[100] rmse=0.019862 lr=0.133822 +[1,0]:INFO:root:Epoch[166] Batch[200] Loss[2.422] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[200] rmse=0.019895 lr=0.133644 +[1,0]:INFO:root:Epoch[166] Batch[300] Loss[3.838] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[300] rmse=0.019864 lr=0.133465 +[1,0]:INFO:root:Epoch[166] Batch[400] Loss[2.832] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[400] rmse=0.019942 lr=0.133287 +[1,0]:INFO:root:Epoch[166] Batch[500] Loss[2.518] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[500] rmse=0.019952 lr=0.133108 +[1,0]:INFO:root:Epoch[166] Batch[600] Loss[2.388] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[600] rmse=0.019962 lr=0.132930 +[1,0]:INFO:root:Epoch[166] Batch[700] Loss[2.677] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[700] rmse=0.019963 lr=0.132751 +[1,0]:INFO:root:Epoch[166] Batch[800] Loss[2.972] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[800] rmse=0.019965 lr=0.132573 +[1,0]:INFO:root:Epoch[166] Batch[900] Loss[4.061] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[900] rmse=0.019965 lr=0.132395 +[1,0]:INFO:root:Epoch[166] Batch[1000] Loss[2.644] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[1000] rmse=0.019983 lr=0.132216 +[1,0]:INFO:root:Epoch[166] Batch[1100] Loss[3.418] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[1100] rmse=0.019991 lr=0.132038 +[1,0]:INFO:root:Epoch[166] Batch[1200] Loss[5.146] +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[1200] rmse=0.019994 lr=0.131860 +[1,0]:INFO:root:Epoch[166] Rank[0] Batch[1251] Time cost=399.41 Train-metric=0.019988 +[1,0]:INFO:root:Epoch[166] Speed: 3207.33 samples/sec +[1,0]:INFO:root:Epoch[167] Batch[100] Loss[3.686] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[100] rmse=0.020065 lr=0.131591 +[1,0]:INFO:root:Epoch[167] Batch[200] Loss[2.567] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[200] rmse=0.019956 lr=0.131413 +[1,0]:INFO:root:Epoch[167] Batch[300] Loss[2.833] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[300] rmse=0.019973 lr=0.131236 +[1,0]:INFO:root:Epoch[167] Batch[400] Loss[2.809] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[400] rmse=0.020004 lr=0.131058 +[1,0]:INFO:root:Epoch[167] Batch[500] Loss[5.042] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[500] rmse=0.019969 lr=0.130880 +[1,0]:INFO:root:Epoch[167] Batch[600] Loss[3.454] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[600] rmse=0.019959 lr=0.130702 +[1,0]:INFO:root:Epoch[167] Batch[700] Loss[2.825] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[700] rmse=0.019956 lr=0.130525 +[1,0]:INFO:root:Epoch[167] Batch[800] Loss[2.681] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[800] rmse=0.019982 lr=0.130347 +[1,0]:INFO:root:Epoch[167] Batch[900] Loss[2.298] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[900] rmse=0.020002 lr=0.130170 +[1,0]:INFO:root:Epoch[167] Batch[1000] Loss[5.095] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[1000] rmse=0.019993 lr=0.129992 +[1,0]:INFO:root:Epoch[167] Batch[1100] Loss[2.619] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[1100] rmse=0.020003 lr=0.129815 +[1,0]:INFO:root:Epoch[167] Batch[1200] Loss[4.088] +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[1200] rmse=0.020004 lr=0.129638 +[1,0]:INFO:root:Epoch[167] Rank[0] Batch[1251] Time cost=398.70 Train-metric=0.020007 +[1,0]:INFO:root:Epoch[167] Speed: 3212.97 samples/sec +[1,0]:INFO:root:Epoch[168] Batch[100] Loss[3.974] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[100] rmse=0.019924 lr=0.129370 +[1,0]:INFO:root:Epoch[168] Batch[200] Loss[2.297] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[200] rmse=0.019870 lr=0.129193 +[1,0]:INFO:root:Epoch[168] Batch[300] Loss[2.515] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[300] rmse=0.019905 lr=0.129016 +[1,0]:INFO:root:Epoch[168] Batch[400] Loss[5.248] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[400] rmse=0.019974 lr=0.128839 +[1,0]:INFO:root:Epoch[168] Batch[500] Loss[2.791] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[500] rmse=0.019977 lr=0.128662 +[1,0]:INFO:root:Epoch[168] Batch[600] Loss[2.570] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[600] rmse=0.019959 lr=0.128485 +[1,0]:INFO:root:Epoch[168] Batch[700] Loss[3.134] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[700] rmse=0.019954 lr=0.128308 +[1,0]:INFO:root:Epoch[168] Batch[800] Loss[5.162] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[800] rmse=0.019960 lr=0.128131 +[1,0]:INFO:root:Epoch[168] Batch[900] Loss[2.654] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[900] rmse=0.019965 lr=0.127955 +[1,0]:INFO:root:Epoch[168] Batch[1000] Loss[4.985] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[1000] rmse=0.019972 lr=0.127778 +[1,0]:INFO:root:Epoch[168] Batch[1100] Loss[2.563] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[1100] rmse=0.019972 lr=0.127601 +[1,0]:INFO:root:Epoch[168] Batch[1200] Loss[4.843] +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[1200] rmse=0.019969 lr=0.127425 +[1,0]:INFO:root:Epoch[168] Rank[0] Batch[1251] Time cost=399.63 Train-metric=0.019973 +[1,0]:INFO:root:Epoch[168] Speed: 3205.56 samples/sec +[1,0]:INFO:root:Epoch[169] Batch[100] Loss[2.376] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[100] rmse=0.020012 lr=0.127159 +[1,0]:INFO:root:Epoch[169] Batch[200] Loss[2.583] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[200] rmse=0.019950 lr=0.126982 +[1,0]:INFO:root:Epoch[169] Batch[300] Loss[2.825] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[300] rmse=0.019918 lr=0.126806 +[1,0]:INFO:root:Epoch[169] Batch[400] Loss[3.515] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[400] rmse=0.019911 lr=0.126630 +[1,0]:INFO:root:Epoch[169] Batch[500] Loss[2.689] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[500] rmse=0.019917 lr=0.126454 +[1,0]:INFO:root:Epoch[169] Batch[600] Loss[2.712] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[600] rmse=0.019946 lr=0.126278 +[1,0]:INFO:root:Epoch[169] Batch[700] Loss[3.310] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[700] rmse=0.019940 lr=0.126102 +[1,0]:INFO:root:Epoch[169] Batch[800] Loss[2.787] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[800] rmse=0.019958 lr=0.125926 +[1,0]:INFO:root:Epoch[169] Batch[900] Loss[2.677] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[900] rmse=0.019963 lr=0.125750 +[1,0]:INFO:root:Epoch[169] Batch[1000] Loss[3.244] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[1000] rmse=0.019966 lr=0.125574 +[1,0]:INFO:root:Epoch[169] Batch[1100] Loss[4.889] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[1100] rmse=0.019950 lr=0.125398 +[1,0]:INFO:root:Epoch[169] Batch[1200] Loss[4.823] +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[1200] rmse=0.019947 lr=0.125222 +[1,0]:INFO:root:Epoch[169] Rank[0] Batch[1251] Time cost=398.96 Train-metric=0.019950 +[1,0]:INFO:root:Epoch[169] Speed: 3210.90 samples/sec +[1,0]:INFO:root:Epoch[169] Rank[0] Validation-accuracy=0.663560 Validation-top_k_accuracy_5=0.874680 +[1,0]:INFO:root:Epoch[170] Batch[100] Loss[2.016] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[100] rmse=0.019700 lr=0.124957 +[1,0]:INFO:root:Epoch[170] Batch[200] Loss[4.366] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[200] rmse=0.019801 lr=0.124782 +[1,0]:INFO:root:Epoch[170] Batch[300] Loss[2.712] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[300] rmse=0.019803 lr=0.124606 +[1,0]:INFO:root:Epoch[170] Batch[400] Loss[4.411] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[400] rmse=0.019838 lr=0.124431 +[1,0]:INFO:root:Epoch[170] Batch[500] Loss[2.532] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[500] rmse=0.019825 lr=0.124256 +[1,0]:INFO:root:Epoch[170] Batch[600] Loss[2.801] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[600] rmse=0.019848 lr=0.124080 +[1,0]:INFO:root:Epoch[170] Batch[700] Loss[2.522] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[700] rmse=0.019885 lr=0.123905 +[1,0]:INFO:root:Epoch[170] Batch[800] Loss[4.866] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[800] rmse=0.019915 lr=0.123730 +[1,0]:INFO:root:Epoch[170] Batch[900] Loss[3.748] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[900] rmse=0.019924 lr=0.123555 +[1,0]:INFO:root:Epoch[170] Batch[1000] Loss[2.645] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[1000] rmse=0.019927 lr=0.123380 +[1,0]:INFO:root:Epoch[170] Batch[1100] Loss[2.645] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[1100] rmse=0.019929 lr=0.123205 +[1,0]:INFO:root:Epoch[170] Batch[1200] Loss[2.955] +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[1200] rmse=0.019932 lr=0.123030 +[1,0]:INFO:root:Epoch[170] Rank[0] Batch[1251] Time cost=399.12 Train-metric=0.019928 +[1,0]:INFO:root:Epoch[170] Speed: 3209.62 samples/sec +[1,0]:INFO:root:Epoch[171] Batch[100] Loss[2.837] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[100] rmse=0.019879 lr=0.122767 +[1,0]:INFO:root:Epoch[171] Batch[200] Loss[2.600] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[200] rmse=0.019838 lr=0.122592 +[1,0]:INFO:root:Epoch[171] Batch[300] Loss[2.604] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[300] rmse=0.019843 lr=0.122417 +[1,0]:INFO:root:Epoch[171] Batch[400] Loss[4.837] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[400] rmse=0.019857 lr=0.122243 +[1,0]:INFO:root:Epoch[171] Batch[500] Loss[3.275] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[500] rmse=0.019883 lr=0.122068 +[1,0]:INFO:root:Epoch[171] Batch[600] Loss[2.741] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[600] rmse=0.019894 lr=0.121894 +[1,0]:INFO:root:Epoch[171] Batch[700] Loss[2.454] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[700] rmse=0.019922 lr=0.121720 +[1,0]:INFO:root:Epoch[171] Batch[800] Loss[3.448] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[800] rmse=0.019933 lr=0.121546 +[1,0]:INFO:root:Epoch[171] Batch[900] Loss[2.919] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[900] rmse=0.019914 lr=0.121371 +[1,0]:INFO:root:Epoch[171] Batch[1000] Loss[3.825] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[1000] rmse=0.019929 lr=0.121197 +[1,0]:INFO:root:Epoch[171] Batch[1100] Loss[4.823] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[1100] rmse=0.019941 lr=0.121023 +[1,0]:INFO:root:Epoch[171] Batch[1200] Loss[3.387] +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[1200] rmse=0.019953 lr=0.120849 +[1,0]:INFO:root:Epoch[171] Rank[0] Batch[1251] Time cost=398.91 Train-metric=0.019944 +[1,0]:INFO:root:Epoch[171] Speed: 3211.32 samples/sec +[1,0]:INFO:root:Epoch[172] Batch[100] Loss[2.630] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[100] rmse=0.019798 lr=0.120587 +[1,0]:INFO:root:Epoch[172] Batch[200] Loss[2.516] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[200] rmse=0.019769 lr=0.120413 +[1,0]:INFO:root:Epoch[172] Batch[300] Loss[5.311] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[300] rmse=0.019844 lr=0.120239 +[1,0]:INFO:root:Epoch[172] Batch[400] Loss[3.260] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[400] rmse=0.019895 lr=0.120066 +[1,0]:INFO:root:Epoch[172] Batch[500] Loss[2.578] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[500] rmse=0.019874 lr=0.119892 +[1,0]:INFO:root:Epoch[172] Batch[600] Loss[4.999] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[600] rmse=0.019876 lr=0.119719 +[1,0]:INFO:root:Epoch[172] Batch[700] Loss[2.613] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[700] rmse=0.019893 lr=0.119545 +[1,0]:INFO:root:Epoch[172] Batch[800] Loss[2.819] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[800] rmse=0.019891 lr=0.119372 +[1,0]:INFO:root:Epoch[172] Batch[900] Loss[2.603] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[900] rmse=0.019894 lr=0.119199 +[1,0]:INFO:root:Epoch[172] Batch[1000] Loss[3.184] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[1000] rmse=0.019885 lr=0.119025 +[1,0]:INFO:root:Epoch[172] Batch[1100] Loss[2.692] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[1100] rmse=0.019878 lr=0.118852 +[1,0]:INFO:root:Epoch[172] Batch[1200] Loss[2.648] +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[1200] rmse=0.019872 lr=0.118679 +[1,0]:INFO:root:Epoch[172] Rank[0] Batch[1251] Time cost=401.36 Train-metric=0.019881 +[1,0]:INFO:root:Epoch[172] Speed: 3191.72 samples/sec +[1,0]:INFO:root:Epoch[173] Batch[100] Loss[2.531] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[100] rmse=0.019803 lr=0.118418 +[1,0]:INFO:root:Epoch[173] Batch[200] Loss[2.874] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[200] rmse=0.019904 lr=0.118245 +[1,0]:INFO:root:Epoch[173] Batch[300] Loss[3.131] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[300] rmse=0.019854 lr=0.118072 +[1,0]:INFO:root:Epoch[173] Batch[400] Loss[3.782] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[400] rmse=0.019914 lr=0.117900 +[1,0]:INFO:root:Epoch[173] Batch[500] Loss[2.816] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[500] rmse=0.019910 lr=0.117727 +[1,0]:INFO:root:Epoch[173] Batch[600] Loss[4.630] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[600] rmse=0.019907 lr=0.117554 +[1,0]:INFO:root:Epoch[173] Batch[700] Loss[5.250] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[700] rmse=0.019884 lr=0.117382 +[1,0]:INFO:root:Epoch[173] Batch[800] Loss[2.743] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[800] rmse=0.019883 lr=0.117209 +[1,0]:INFO:root:Epoch[173] Batch[900] Loss[2.736] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[900] rmse=0.019903 lr=0.117037 +[1,0]:INFO:root:Epoch[173] Batch[1000] Loss[2.899] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[1000] rmse=0.019908 lr=0.116865 +[1,0]:INFO:root:Epoch[173] Batch[1100] Loss[3.230] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[1100] rmse=0.019918 lr=0.116693 +[1,0]:INFO:root:Epoch[173] Batch[1200] Loss[4.559] +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[1200] rmse=0.019933 lr=0.116521 +[1,0]:INFO:root:Epoch[173] Rank[0] Batch[1251] Time cost=402.18 Train-metric=0.019924 +[1,0]:INFO:root:Epoch[173] Speed: 3185.22 samples/sec +[1,0]:INFO:root:Epoch[174] Batch[100] Loss[2.680] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[100] rmse=0.019791 lr=0.116261 +[1,0]:INFO:root:Epoch[174] Batch[200] Loss[2.783] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[200] rmse=0.019816 lr=0.116089 +[1,0]:INFO:root:Epoch[174] Batch[300] Loss[2.376] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[300] rmse=0.019760 lr=0.115917 +[1,0]:INFO:root:Epoch[174] Batch[400] Loss[2.681] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[400] rmse=0.019744 lr=0.115745 +[1,0]:INFO:root:Epoch[174] Batch[500] Loss[2.570] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[500] rmse=0.019780 lr=0.115573 +[1,0]:INFO:root:Epoch[174] Batch[600] Loss[4.721] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[600] rmse=0.019805 lr=0.115402 +[1,0]:INFO:root:Epoch[174] Batch[700] Loss[2.842] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[700] rmse=0.019825 lr=0.115230 +[1,0]:INFO:root:Epoch[174] Batch[800] Loss[4.467] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[800] rmse=0.019842 lr=0.115059 +[1,0]:INFO:root:Epoch[174] Batch[900] Loss[3.430] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[900] rmse=0.019833 lr=0.114887 +[1,0]:INFO:root:Epoch[174] Batch[1000] Loss[5.032] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[1000] rmse=0.019854 lr=0.114716 +[1,0]:INFO:root:Epoch[174] Batch[1100] Loss[2.660] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[1100] rmse=0.019874 lr=0.114545 +[1,0]:INFO:root:Epoch[174] Batch[1200] Loss[2.790] +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[1200] rmse=0.019891 lr=0.114374 +[1,0]:INFO:root:Epoch[174] Rank[0] Batch[1251] Time cost=402.32 Train-metric=0.019886 +[1,0]:INFO:root:Epoch[174] Speed: 3184.07 samples/sec +[1,0]:INFO:root:Epoch[174] Rank[0] Validation-accuracy=0.669840 Validation-top_k_accuracy_5=0.880340 +[1,0]:INFO:root:Epoch[175] Batch[100] Loss[2.652] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[100] rmse=0.019703 lr=0.114115 +[1,0]:INFO:root:Epoch[175] Batch[200] Loss[2.311] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[200] rmse=0.019643 lr=0.113944 +[1,0]:INFO:root:Epoch[175] Batch[300] Loss[2.852] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[300] rmse=0.019689 lr=0.113773 +[1,0]:INFO:root:Epoch[175] Batch[400] Loss[2.993] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[400] rmse=0.019736 lr=0.113602 +[1,0]:INFO:root:Epoch[175] Batch[500] Loss[4.791] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[500] rmse=0.019737 lr=0.113432 +[1,0]:INFO:root:Epoch[175] Batch[600] Loss[2.588] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[600] rmse=0.019730 lr=0.113261 +[1,0]:INFO:root:Epoch[175] Batch[700] Loss[2.692] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[700] rmse=0.019738 lr=0.113090 +[1,0]:INFO:root:Epoch[175] Batch[800] Loss[3.464] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[800] rmse=0.019773 lr=0.112920 +[1,0]:INFO:root:Epoch[175] Batch[900] Loss[2.773] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[900] rmse=0.019789 lr=0.112749 +[1,0]:INFO:root:Epoch[175] Batch[1000] Loss[2.971] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[1000] rmse=0.019792 lr=0.112579 +[1,0]:INFO:root:Epoch[175] Batch[1100] Loss[2.588] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[1100] rmse=0.019795 lr=0.112409 +[1,0]:INFO:root:Epoch[175] Batch[1200] Loss[2.612] +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[1200] rmse=0.019810 lr=0.112239 +[1,0]:INFO:root:Epoch[175] Rank[0] Batch[1251] Time cost=402.05 Train-metric=0.019806 +[1,0]:INFO:root:Epoch[175] Speed: 3186.22 samples/sec +[1,0]:INFO:root:Epoch[176] Batch[100] Loss[2.435] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[100] rmse=0.019924 lr=0.111982 +[1,0]:INFO:root:Epoch[176] Batch[200] Loss[2.526] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[200] rmse=0.019841 lr=0.111812 +[1,0]:INFO:root:Epoch[176] Batch[300] Loss[4.743] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[300] rmse=0.019850 lr=0.111642 +[1,0]:INFO:root:Epoch[176] Batch[400] Loss[3.237] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[400] rmse=0.019828 lr=0.111472 +[1,0]:INFO:root:Epoch[176] Batch[500] Loss[5.188] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[500] rmse=0.019807 lr=0.111302 +[1,0]:INFO:root:Epoch[176] Batch[600] Loss[3.429] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[600] rmse=0.019846 lr=0.111132 +[1,0]:INFO:root:Epoch[176] Batch[700] Loss[3.748] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[700] rmse=0.019846 lr=0.110963 +[1,0]:INFO:root:Epoch[176] Batch[800] Loss[5.019] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[800] rmse=0.019863 lr=0.110793 +[1,0]:INFO:root:Epoch[176] Batch[900] Loss[5.048] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[900] rmse=0.019859 lr=0.110624 +[1,0]:INFO:root:Epoch[176] Batch[1000] Loss[3.069] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[1000] rmse=0.019852 lr=0.110454 +[1,0]:INFO:root:Epoch[176] Batch[1100] Loss[3.071] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[1100] rmse=0.019844 lr=0.110285 +[1,0]:INFO:root:Epoch[176] Batch[1200] Loss[3.147] +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[1200] rmse=0.019862 lr=0.110116 +[1,0]:INFO:root:Epoch[176] Rank[0] Batch[1251] Time cost=400.02 Train-metric=0.019871 +[1,0]:INFO:root:Epoch[176] Speed: 3202.36 samples/sec +[1,0]:INFO:root:Epoch[177] Batch[100] Loss[2.764] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[100] rmse=0.019630 lr=0.109861 +[1,0]:INFO:root:Epoch[177] Batch[200] Loss[2.612] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[200] rmse=0.019770 lr=0.109692 +[1,0]:INFO:root:Epoch[177] Batch[300] Loss[4.360] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[300] rmse=0.019820 lr=0.109523 +[1,0]:INFO:root:Epoch[177] Batch[400] Loss[2.681] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[400] rmse=0.019786 lr=0.109354 +[1,0]:INFO:root:Epoch[177] Batch[500] Loss[2.591] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[500] rmse=0.019813 lr=0.109185 +[1,0]:INFO:root:Epoch[177] Batch[600] Loss[5.038] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[600] rmse=0.019808 lr=0.109016 +[1,0]:INFO:root:Epoch[177] Batch[700] Loss[2.389] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[700] rmse=0.019802 lr=0.108848 +[1,0]:INFO:root:Epoch[177] Batch[800] Loss[2.522] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[800] rmse=0.019802 lr=0.108679 +[1,0]:INFO:root:Epoch[177] Batch[900] Loss[2.968] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[900] rmse=0.019826 lr=0.108511 +[1,0]:INFO:root:Epoch[177] Batch[1000] Loss[2.609] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[1000] rmse=0.019825 lr=0.108342 +[1,0]:INFO:root:Epoch[177] Batch[1100] Loss[3.836] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[1100] rmse=0.019842 lr=0.108174 +[1,0]:INFO:root:Epoch[177] Batch[1200] Loss[4.361] +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[1200] rmse=0.019838 lr=0.108006 +[1,0]:INFO:root:Epoch[177] Rank[0] Batch[1251] Time cost=400.91 Train-metric=0.019835 +[1,0]:INFO:root:Epoch[177] Speed: 3195.25 samples/sec +[1,0]:INFO:root:Epoch[178] Batch[100] Loss[4.785] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[100] rmse=0.019715 lr=0.107752 +[1,0]:INFO:root:Epoch[178] Batch[200] Loss[2.626] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[200] rmse=0.019699 lr=0.107584 +[1,0]:INFO:root:Epoch[178] Batch[300] Loss[4.103] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[300] rmse=0.019670 lr=0.107416 +[1,0]:INFO:root:Epoch[178] Batch[400] Loss[4.938] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[400] rmse=0.019651 lr=0.107248 +[1,0]:INFO:root:Epoch[178] Batch[500] Loss[2.782] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[500] rmse=0.019696 lr=0.107081 +[1,0]:INFO:root:Epoch[178] Batch[600] Loss[2.632] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[600] rmse=0.019710 lr=0.106913 +[1,0]:INFO:root:Epoch[178] Batch[700] Loss[2.536] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[700] rmse=0.019729 lr=0.106745 +[1,0]:INFO:root:Epoch[178] Batch[800] Loss[4.524] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[800] rmse=0.019753 lr=0.106578 +[1,0]:INFO:root:Epoch[178] Batch[900] Loss[3.815] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[900] rmse=0.019768 lr=0.106411 +[1,0]:INFO:root:Epoch[178] Batch[1000] Loss[2.473] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[1000] rmse=0.019769 lr=0.106243 +[1,0]:INFO:root:Epoch[178] Batch[1100] Loss[2.571] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[1100] rmse=0.019790 lr=0.106076 +[1,0]:INFO:root:Epoch[178] Batch[1200] Loss[4.631] +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[1200] rmse=0.019789 lr=0.105909 +[1,0]:INFO:root:Epoch[178] Rank[0] Batch[1251] Time cost=399.04 Train-metric=0.019790 +[1,0]:INFO:root:Epoch[178] Speed: 3210.25 samples/sec +[1,0]:INFO:root:Epoch[179] Batch[100] Loss[2.453] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[100] rmse=0.019583 lr=0.105657 +[1,0]:INFO:root:Epoch[179] Batch[200] Loss[2.813] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[200] rmse=0.019690 lr=0.105490 +[1,0]:INFO:root:Epoch[179] Batch[300] Loss[2.675] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[300] rmse=0.019743 lr=0.105323 +[1,0]:INFO:root:Epoch[179] Batch[400] Loss[2.925] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[400] rmse=0.019725 lr=0.105156 +[1,0]:INFO:root:Epoch[179] Batch[500] Loss[2.477] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[500] rmse=0.019741 lr=0.104989 +[1,0]:INFO:root:Epoch[179] Batch[600] Loss[2.522] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[600] rmse=0.019746 lr=0.104823 +[1,0]:INFO:root:Epoch[179] Batch[700] Loss[3.501] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[700] rmse=0.019753 lr=0.104656 +[1,0]:INFO:root:Epoch[179] Batch[800] Loss[2.500] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[800] rmse=0.019759 lr=0.104490 +[1,0]:INFO:root:Epoch[179] Batch[900] Loss[4.839] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[900] rmse=0.019762 lr=0.104323 +[1,0]:INFO:root:Epoch[179] Batch[1000] Loss[2.583] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[1000] rmse=0.019764 lr=0.104157 +[1,0]:INFO:root:Epoch[179] Batch[1100] Loss[3.936] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[1100] rmse=0.019775 lr=0.103991 +[1,0]:INFO:root:Epoch[179] Batch[1200] Loss[3.072] +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[1200] rmse=0.019783 lr=0.103825 +[1,0]:INFO:root:Epoch[179] Rank[0] Batch[1251] Time cost=400.20 Train-metric=0.019793 +[1,0]:INFO:root:Epoch[179] Speed: 3200.96 samples/sec +[1,0]:INFO:root:Epoch[179] Rank[0] Validation-accuracy=0.677220 Validation-top_k_accuracy_5=0.880600 +[1,0]:INFO:root:Epoch[180] Batch[100] Loss[2.526] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[100] rmse=0.019732 lr=0.103574 +[1,0]:INFO:root:Epoch[180] Batch[200] Loss[2.628] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[200] rmse=0.019670 lr=0.103408 +[1,0]:INFO:root:Epoch[180] Batch[300] Loss[2.595] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[300] rmse=0.019704 lr=0.103243 +[1,0]:INFO:root:Epoch[180] Batch[400] Loss[3.280] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[400] rmse=0.019724 lr=0.103077 +[1,0]:INFO:root:Epoch[180] Batch[500] Loss[4.102] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[500] rmse=0.019754 lr=0.102911 +[1,0]:INFO:root:Epoch[180] Batch[600] Loss[3.379] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[600] rmse=0.019755 lr=0.102746 +[1,0]:INFO:root:Epoch[180] Batch[700] Loss[2.551] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[700] rmse=0.019743 lr=0.102580 +[1,0]:INFO:root:Epoch[180] Batch[800] Loss[4.468] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[800] rmse=0.019737 lr=0.102415 +[1,0]:INFO:root:Epoch[180] Batch[900] Loss[4.049] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[900] rmse=0.019744 lr=0.102250 +[1,0]:INFO:root:Epoch[180] Batch[1000] Loss[4.153] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[1000] rmse=0.019727 lr=0.102085 +[1,0]:INFO:root:Epoch[180] Batch[1100] Loss[2.542] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[1100] rmse=0.019751 lr=0.101919 +[1,0]:INFO:root:Epoch[180] Batch[1200] Loss[4.052] +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[1200] rmse=0.019747 lr=0.101754 +[1,0]:INFO:root:Epoch[180] Rank[0] Batch[1251] Time cost=398.25 Train-metric=0.019749 +[1,0]:INFO:root:Epoch[180] Speed: 3216.60 samples/sec +[1,0]:INFO:root:Epoch[181] Batch[100] Loss[2.622] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[100] rmse=0.019692 lr=0.101505 +[1,0]:INFO:root:Epoch[181] Batch[200] Loss[3.363] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[200] rmse=0.019692 lr=0.101341 +[1,0]:INFO:root:Epoch[181] Batch[300] Loss[2.699] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[300] rmse=0.019670 lr=0.101176 +[1,0]:INFO:root:Epoch[181] Batch[400] Loss[2.645] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[400] rmse=0.019649 lr=0.101011 +[1,0]:INFO:root:Epoch[181] Batch[500] Loss[2.634] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[500] rmse=0.019670 lr=0.100847 +[1,0]:INFO:root:Epoch[181] Batch[600] Loss[5.049] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[600] rmse=0.019676 lr=0.100682 +[1,0]:INFO:root:Epoch[181] Batch[700] Loss[2.350] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[700] rmse=0.019671 lr=0.100518 +[1,0]:INFO:root:Epoch[181] Batch[800] Loss[2.727] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[800] rmse=0.019668 lr=0.100354 +[1,0]:INFO:root:Epoch[181] Batch[900] Loss[2.657] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[900] rmse=0.019692 lr=0.100190 +[1,0]:INFO:root:Epoch[181] Batch[1000] Loss[4.876] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[1000] rmse=0.019715 lr=0.100026 +[1,0]:INFO:root:Epoch[181] Batch[1100] Loss[4.580] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[1100] rmse=0.019724 lr=0.099862 +[1,0]:INFO:root:Epoch[181] Batch[1200] Loss[4.721] +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[1200] rmse=0.019725 lr=0.099698 +[1,0]:INFO:root:Epoch[181] Rank[0] Batch[1251] Time cost=399.16 Train-metric=0.019716 +[1,0]:INFO:root:Epoch[181] Speed: 3209.27 samples/sec +[1,0]:INFO:root:Epoch[182] Batch[100] Loss[2.742] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[100] rmse=0.019599 lr=0.099451 +[1,0]:INFO:root:Epoch[182] Batch[200] Loss[5.080] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[200] rmse=0.019565 lr=0.099287 +[1,0]:INFO:root:Epoch[182] Batch[300] Loss[2.847] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[300] rmse=0.019610 lr=0.099123 +[1,0]:INFO:root:Epoch[182] Batch[400] Loss[4.859] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[400] rmse=0.019611 lr=0.098960 +[1,0]:INFO:root:Epoch[182] Batch[500] Loss[2.471] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[500] rmse=0.019635 lr=0.098796 +[1,0]:INFO:root:Epoch[182] Batch[600] Loss[2.528] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[600] rmse=0.019680 lr=0.098633 +[1,0]:INFO:root:Epoch[182] Batch[700] Loss[3.794] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[700] rmse=0.019710 lr=0.098470 +[1,0]:INFO:root:Epoch[182] Batch[800] Loss[2.696] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[800] rmse=0.019715 lr=0.098307 +[1,0]:INFO:root:Epoch[182] Batch[900] Loss[2.828] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[900] rmse=0.019696 lr=0.098144 +[1,0]:INFO:root:Epoch[182] Batch[1000] Loss[3.016] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[1000] rmse=0.019691 lr=0.097981 +[1,0]:INFO:root:Epoch[182] Batch[1100] Loss[2.320] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[1100] rmse=0.019705 lr=0.097818 +[1,0]:INFO:root:Epoch[182] Batch[1200] Loss[2.812] +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[1200] rmse=0.019700 lr=0.097655 +[1,0]:INFO:root:Epoch[182] Rank[0] Batch[1251] Time cost=398.94 Train-metric=0.019697 +[1,0]:INFO:root:Epoch[182] Speed: 3211.08 samples/sec +[1,0]:INFO:root:Epoch[183] Batch[100] Loss[5.002] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[100] rmse=0.019642 lr=0.097410 +[1,0]:INFO:root:Epoch[183] Batch[200] Loss[2.830] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[200] rmse=0.019562 lr=0.097247 +[1,0]:INFO:root:Epoch[183] Batch[300] Loss[2.405] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[300] rmse=0.019580 lr=0.097085 +[1,0]:INFO:root:Epoch[183] Batch[400] Loss[2.928] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[400] rmse=0.019585 lr=0.096922 +[1,0]:INFO:root:Epoch[183] Batch[500] Loss[2.476] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[500] rmse=0.019614 lr=0.096760 +[1,0]:INFO:root:Epoch[183] Batch[600] Loss[2.470] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[600] rmse=0.019612 lr=0.096598 +[1,0]:INFO:root:Epoch[183] Batch[700] Loss[4.808] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[700] rmse=0.019626 lr=0.096436 +[1,0]:INFO:root:Epoch[183] Batch[800] Loss[2.576] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[800] rmse=0.019616 lr=0.096274 +[1,0]:INFO:root:Epoch[183] Batch[900] Loss[2.666] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[900] rmse=0.019637 lr=0.096112 +[1,0]:INFO:root:Epoch[183] Batch[1000] Loss[4.919] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[1000] rmse=0.019655 lr=0.095950 +[1,0]:INFO:root:Epoch[183] Batch[1100] Loss[3.399] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[1100] rmse=0.019671 lr=0.095789 +[1,0]:INFO:root:Epoch[183] Batch[1200] Loss[3.953] +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[1200] rmse=0.019673 lr=0.095627 +[1,0]:INFO:root:Epoch[183] Rank[0] Batch[1251] Time cost=399.27 Train-metric=0.019674 +[1,0]:INFO:root:Epoch[183] Speed: 3208.44 samples/sec +[1,0]:INFO:root:Epoch[184] Batch[100] Loss[2.384] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[100] rmse=0.019477 lr=0.095383 +[1,0]:INFO:root:Epoch[184] Batch[200] Loss[2.314] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[200] rmse=0.019439 lr=0.095222 +[1,0]:INFO:root:Epoch[184] Batch[300] Loss[2.611] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[300] rmse=0.019485 lr=0.095061 +[1,0]:INFO:root:Epoch[184] Batch[400] Loss[4.652] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[400] rmse=0.019535 lr=0.094899 +[1,0]:INFO:root:Epoch[184] Batch[500] Loss[2.979] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[500] rmse=0.019579 lr=0.094738 +[1,0]:INFO:root:Epoch[184] Batch[600] Loss[3.448] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[600] rmse=0.019571 lr=0.094577 +[1,0]:INFO:root:Epoch[184] Batch[700] Loss[2.401] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[700] rmse=0.019582 lr=0.094417 +[1,0]:INFO:root:Epoch[184] Batch[800] Loss[3.187] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[800] rmse=0.019601 lr=0.094256 +[1,0]:INFO:root:Epoch[184] Batch[900] Loss[2.420] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[900] rmse=0.019611 lr=0.094095 +[1,0]:INFO:root:Epoch[184] Batch[1000] Loss[3.447] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[1000] rmse=0.019629 lr=0.093934 +[1,0]:INFO:root:Epoch[184] Batch[1100] Loss[3.678] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[1100] rmse=0.019613 lr=0.093774 +[1,0]:INFO:root:Epoch[184] Batch[1200] Loss[2.431] +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[1200] rmse=0.019614 lr=0.093614 +[1,0]:INFO:root:Epoch[184] Rank[0] Batch[1251] Time cost=399.48 Train-metric=0.019616 +[1,0]:INFO:root:Epoch[184] Speed: 3206.71 samples/sec +[1,0]:INFO:root:Epoch[184] Rank[0] Validation-accuracy=0.683280 Validation-top_k_accuracy_5=0.886280 +[1,0]:INFO:root:Epoch[185] Batch[100] Loss[2.622] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[100] rmse=0.019698 lr=0.093371 +[1,0]:INFO:root:Epoch[185] Batch[200] Loss[4.981] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[200] rmse=0.019691 lr=0.093211 +[1,0]:INFO:root:Epoch[185] Batch[300] Loss[2.476] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[300] rmse=0.019690 lr=0.093051 +[1,0]:INFO:root:Epoch[185] Batch[400] Loss[2.759] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[400] rmse=0.019676 lr=0.092891 +[1,0]:INFO:root:Epoch[185] Batch[500] Loss[2.411] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[500] rmse=0.019653 lr=0.092731 +[1,0]:INFO:root:Epoch[185] Batch[600] Loss[3.478] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[600] rmse=0.019675 lr=0.092572 +[1,0]:INFO:root:Epoch[185] Batch[700] Loss[2.735] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[700] rmse=0.019680 lr=0.092412 +[1,0]:INFO:root:Epoch[185] Batch[800] Loss[3.261] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[800] rmse=0.019679 lr=0.092252 +[1,0]:INFO:root:Epoch[185] Batch[900] Loss[2.575] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[900] rmse=0.019680 lr=0.092093 +[1,0]:INFO:root:Epoch[185] Batch[1000] Loss[3.667] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[1000] rmse=0.019680 lr=0.091933 +[1,0]:INFO:root:Epoch[185] Batch[1100] Loss[4.797] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[1100] rmse=0.019677 lr=0.091774 +[1,0]:INFO:root:Epoch[185] Batch[1200] Loss[2.723] +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[1200] rmse=0.019672 lr=0.091615 +[1,0]:INFO:root:Epoch[185] Rank[0] Batch[1251] Time cost=398.62 Train-metric=0.019669 +[1,0]:INFO:root:Epoch[185] Speed: 3213.67 samples/sec +[1,0]:INFO:root:Epoch[186] Batch[100] Loss[2.652] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[100] rmse=0.019692 lr=0.091375 +[1,0]:INFO:root:Epoch[186] Batch[200] Loss[2.856] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[200] rmse=0.019569 lr=0.091216 +[1,0]:INFO:root:Epoch[186] Batch[300] Loss[4.685] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[300] rmse=0.019559 lr=0.091057 +[1,0]:INFO:root:Epoch[186] Batch[400] Loss[2.675] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[400] rmse=0.019567 lr=0.090898 +[1,0]:INFO:root:Epoch[186] Batch[500] Loss[4.075] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[500] rmse=0.019529 lr=0.090739 +[1,0]:INFO:root:Epoch[186] Batch[600] Loss[5.139] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[600] rmse=0.019528 lr=0.090581 +[1,0]:INFO:root:Epoch[186] Batch[700] Loss[2.626] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[700] rmse=0.019548 lr=0.090422 +[1,0]:INFO:root:Epoch[186] Batch[800] Loss[3.088] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[800] rmse=0.019525 lr=0.090264 +[1,0]:INFO:root:Epoch[186] Batch[900] Loss[2.967] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[900] rmse=0.019537 lr=0.090106 +[1,0]:INFO:root:Epoch[186] Batch[1000] Loss[2.564] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[1000] rmse=0.019554 lr=0.089948 +[1,0]:INFO:root:Epoch[186] Batch[1100] Loss[4.287] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[1100] rmse=0.019560 lr=0.089789 +[1,0]:INFO:root:Epoch[186] Batch[1200] Loss[2.711] +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[1200] rmse=0.019574 lr=0.089631 +[1,0]:INFO:root:Epoch[186] Rank[0] Batch[1251] Time cost=399.26 Train-metric=0.019583 +[1,0]:INFO:root:Epoch[186] Speed: 3208.50 samples/sec +[1,0]:INFO:root:Epoch[187] Batch[100] Loss[4.557] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[100] rmse=0.019580 lr=0.089393 +[1,0]:INFO:root:Epoch[187] Batch[200] Loss[3.309] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[200] rmse=0.019593 lr=0.089235 +[1,0]:INFO:root:Epoch[187] Batch[300] Loss[2.629] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[300] rmse=0.019564 lr=0.089078 +[1,0]:INFO:root:Epoch[187] Batch[400] Loss[2.401] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[400] rmse=0.019562 lr=0.088920 +[1,0]:INFO:root:Epoch[187] Batch[500] Loss[3.028] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[500] rmse=0.019581 lr=0.088763 +[1,0]:INFO:root:Epoch[187] Batch[600] Loss[4.766] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[600] rmse=0.019592 lr=0.088605 +[1,0]:INFO:root:Epoch[187] Batch[700] Loss[2.442] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[700] rmse=0.019600 lr=0.088448 +[1,0]:INFO:root:Epoch[187] Batch[800] Loss[2.544] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[800] rmse=0.019613 lr=0.088291 +[1,0]:INFO:root:Epoch[187] Batch[900] Loss[4.682] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[900] rmse=0.019601 lr=0.088134 +[1,0]:INFO:root:Epoch[187] Batch[1000] Loss[3.086] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[1000] rmse=0.019611 lr=0.087977 +[1,0]:INFO:root:Epoch[187] Batch[1100] Loss[2.760] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[1100] rmse=0.019616 lr=0.087820 +[1,0]:INFO:root:Epoch[187] Batch[1200] Loss[4.116] +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[1200] rmse=0.019605 lr=0.087664 +[1,0]:INFO:root:Epoch[187] Rank[0] Batch[1251] Time cost=399.42 Train-metric=0.019603 +[1,0]:INFO:root:Epoch[187] Speed: 3207.18 samples/sec +[1,0]:INFO:root:Epoch[188] Batch[100] Loss[4.732] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[100] rmse=0.019445 lr=0.087427 +[1,0]:INFO:root:Epoch[188] Batch[200] Loss[2.767] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[200] rmse=0.019503 lr=0.087271 +[1,0]:INFO:root:Epoch[188] Batch[300] Loss[2.952] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[300] rmse=0.019482 lr=0.087114 +[1,0]:INFO:root:Epoch[188] Batch[400] Loss[2.681] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[400] rmse=0.019486 lr=0.086958 +[1,0]:INFO:root:Epoch[188] Batch[500] Loss[3.114] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[500] rmse=0.019514 lr=0.086802 +[1,0]:INFO:root:Epoch[188] Batch[600] Loss[4.881] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[600] rmse=0.019523 lr=0.086646 +[1,0]:INFO:root:Epoch[188] Batch[700] Loss[2.651] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[700] rmse=0.019533 lr=0.086490 +[1,0]:INFO:root:Epoch[188] Batch[800] Loss[2.737] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[800] rmse=0.019551 lr=0.086334 +[1,0]:INFO:root:Epoch[188] Batch[900] Loss[3.804] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[900] rmse=0.019573 lr=0.086178 +[1,0]:INFO:root:Epoch[188] Batch[1000] Loss[2.885] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[1000] rmse=0.019559 lr=0.086022 +[1,0]:INFO:root:Epoch[188] Batch[1100] Loss[3.014] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[1100] rmse=0.019561 lr=0.085867 +[1,0]:INFO:root:Epoch[188] Batch[1200] Loss[2.832] +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[1200] rmse=0.019563 lr=0.085711 +[1,0]:INFO:root:Epoch[188] Rank[0] Batch[1251] Time cost=400.32 Train-metric=0.019572 +[1,0]:INFO:root:Epoch[188] Speed: 3200.02 samples/sec +[1,0]:INFO:root:Epoch[189] Batch[100] Loss[2.659] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[100] rmse=0.019396 lr=0.085477 +[1,0]:INFO:root:Epoch[189] Batch[200] Loss[4.683] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[200] rmse=0.019354 lr=0.085322 +[1,0]:INFO:root:Epoch[189] Batch[300] Loss[2.444] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[300] rmse=0.019408 lr=0.085166 +[1,0]:INFO:root:Epoch[189] Batch[400] Loss[4.681] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[400] rmse=0.019425 lr=0.085012 +[1,0]:INFO:root:Epoch[189] Batch[500] Loss[4.784] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[500] rmse=0.019447 lr=0.084857 +[1,0]:INFO:root:Epoch[189] Batch[600] Loss[4.084] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[600] rmse=0.019448 lr=0.084702 +[1,0]:INFO:root:Epoch[189] Batch[700] Loss[3.829] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[700] rmse=0.019461 lr=0.084547 +[1,0]:INFO:root:Epoch[189] Batch[800] Loss[2.469] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[800] rmse=0.019475 lr=0.084393 +[1,0]:INFO:root:Epoch[189] Batch[900] Loss[2.441] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[900] rmse=0.019488 lr=0.084238 +[1,0]:INFO:root:Epoch[189] Batch[1000] Loss[2.474] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[1000] rmse=0.019472 lr=0.084084 +[1,0]:INFO:root:Epoch[189] Batch[1100] Loss[5.087] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[1100] rmse=0.019493 lr=0.083929 +[1,0]:INFO:root:Epoch[189] Batch[1200] Loss[2.360] +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[1200] rmse=0.019498 lr=0.083775 +[1,0]:INFO:root:Epoch[189] Rank[0] Batch[1251] Time cost=399.63 Train-metric=0.019501 +[1,0]:INFO:root:Epoch[189] Speed: 3205.50 samples/sec +[1,0]:INFO:root:Epoch[189] Rank[0] Validation-accuracy=0.685360 Validation-top_k_accuracy_5=0.887720 +[1,0]:INFO:root:Epoch[190] Batch[100] Loss[2.561] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[100] rmse=0.019361 lr=0.083543 +[1,0]:INFO:root:Epoch[190] Batch[200] Loss[2.671] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[200] rmse=0.019344 lr=0.083389 +[1,0]:INFO:root:Epoch[190] Batch[300] Loss[3.975] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[300] rmse=0.019376 lr=0.083235 +[1,0]:INFO:root:Epoch[190] Batch[400] Loss[4.282] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[400] rmse=0.019408 lr=0.083081 +[1,0]:INFO:root:Epoch[190] Batch[500] Loss[3.060] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[500] rmse=0.019403 lr=0.082928 +[1,0]:INFO:root:Epoch[190] Batch[600] Loss[3.314] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[600] rmse=0.019463 lr=0.082774 +[1,0]:INFO:root:Epoch[190] Batch[700] Loss[2.451] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[700] rmse=0.019469 lr=0.082621 +[1,0]:INFO:root:Epoch[190] Batch[800] Loss[4.566] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[800] rmse=0.019472 lr=0.082467 +[1,0]:INFO:root:Epoch[190] Batch[900] Loss[4.436] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[900] rmse=0.019481 lr=0.082314 +[1,0]:INFO:root:Epoch[190] Batch[1000] Loss[2.775] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[1000] rmse=0.019486 lr=0.082161 +[1,0]:INFO:root:Epoch[190] Batch[1100] Loss[2.787] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[1100] rmse=0.019500 lr=0.082008 +[1,0]:INFO:root:Epoch[190] Batch[1200] Loss[4.274] +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[1200] rmse=0.019507 lr=0.081855 +[1,0]:INFO:root:Epoch[190] Rank[0] Batch[1251] Time cost=398.79 Train-metric=0.019514 +[1,0]:INFO:root:Epoch[190] Speed: 3212.24 samples/sec +[1,0]:INFO:root:Epoch[191] Batch[100] Loss[2.539] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[100] rmse=0.019310 lr=0.081625 +[1,0]:INFO:root:Epoch[191] Batch[200] Loss[2.564] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[200] rmse=0.019424 lr=0.081472 +[1,0]:INFO:root:Epoch[191] Batch[300] Loss[2.723] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[300] rmse=0.019444 lr=0.081320 +[1,0]:INFO:root:Epoch[191] Batch[400] Loss[2.307] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[400] rmse=0.019432 lr=0.081167 +[1,0]:INFO:root:Epoch[191] Batch[500] Loss[2.934] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[500] rmse=0.019417 lr=0.081015 +[1,0]:INFO:root:Epoch[191] Batch[600] Loss[2.872] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[600] rmse=0.019423 lr=0.080863 +[1,0]:INFO:root:Epoch[191] Batch[700] Loss[2.525] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[700] rmse=0.019450 lr=0.080711 +[1,0]:INFO:root:Epoch[191] Batch[800] Loss[2.609] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[800] rmse=0.019453 lr=0.080559 +[1,0]:INFO:root:Epoch[191] Batch[900] Loss[2.304] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[900] rmse=0.019468 lr=0.080407 +[1,0]:INFO:root:Epoch[191] Batch[1000] Loss[4.266] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[1000] rmse=0.019472 lr=0.080255 +[1,0]:INFO:root:Epoch[191] Batch[1100] Loss[2.684] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[1100] rmse=0.019465 lr=0.080104 +[1,0]:INFO:root:Epoch[191] Batch[1200] Loss[2.541] +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[1200] rmse=0.019479 lr=0.079952 +[1,0]:INFO:root:Epoch[191] Rank[0] Batch[1251] Time cost=399.33 Train-metric=0.019487 +[1,0]:INFO:root:Epoch[191] Speed: 3207.92 samples/sec +[1,0]:INFO:root:Epoch[192] Batch[100] Loss[2.465] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[100] rmse=0.019266 lr=0.079724 +[1,0]:INFO:root:Epoch[192] Batch[200] Loss[2.682] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[200] rmse=0.019386 lr=0.079572 +[1,0]:INFO:root:Epoch[192] Batch[300] Loss[2.647] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[300] rmse=0.019394 lr=0.079421 +[1,0]:INFO:root:Epoch[192] Batch[400] Loss[2.368] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[400] rmse=0.019453 lr=0.079270 +[1,0]:INFO:root:Epoch[192] Batch[500] Loss[2.542] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[500] rmse=0.019440 lr=0.079119 +[1,2]:[ip-172-31-29-212][[55333,1],2][btl_tcp.c:559:mca_btl_tcp_recv_blocking] recv(116) failed: Connection reset by peer (104) +[1,0]:INFO:root:Epoch[192] Batch[600] Loss[4.542] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[600] rmse=0.019413 lr=0.078968 +[1,0]:INFO:root:Epoch[192] Batch[700] Loss[3.157] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[700] rmse=0.019420 lr=0.078818 +[1,0]:INFO:root:Epoch[192] Batch[800] Loss[4.956] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[800] rmse=0.019442 lr=0.078667 +[1,0]:INFO:root:Epoch[192] Batch[900] Loss[4.319] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[900] rmse=0.019437 lr=0.078517 +[1,0]:INFO:root:Epoch[192] Batch[1000] Loss[4.140] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[1000] rmse=0.019429 lr=0.078366 +[1,0]:INFO:root:Epoch[192] Batch[1100] Loss[4.664] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[1100] rmse=0.019433 lr=0.078216 +[1,0]:INFO:root:Epoch[192] Batch[1200] Loss[2.564] +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[1200] rmse=0.019437 lr=0.078066 +[1,0]:INFO:root:Epoch[192] Rank[0] Batch[1251] Time cost=398.52 Train-metric=0.019438 +[1,0]:INFO:root:Epoch[192] Speed: 3214.47 samples/sec +[1,0]:INFO:root:Epoch[193] Batch[100] Loss[2.590] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[100] rmse=0.019240 lr=0.077839 +[1,0]:INFO:root:Epoch[193] Batch[200] Loss[2.512] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[200] rmse=0.019280 lr=0.077689 +[1,0]:INFO:root:Epoch[193] Batch[300] Loss[2.602] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[300] rmse=0.019364 lr=0.077540 +[1,0]:INFO:root:Epoch[193] Batch[400] Loss[4.966] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[400] rmse=0.019381 lr=0.077390 +[1,0]:INFO:root:Epoch[193] Batch[500] Loss[4.897] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[500] rmse=0.019376 lr=0.077240 +[1,0]:INFO:root:Epoch[193] Batch[600] Loss[3.420] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[600] rmse=0.019372 lr=0.077091 +[1,0]:INFO:root:Epoch[193] Batch[700] Loss[2.587] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[700] rmse=0.019384 lr=0.076942 +[1,0]:INFO:root:Epoch[193] Batch[800] Loss[5.273] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[800] rmse=0.019403 lr=0.076792 +[1,0]:INFO:root:Epoch[193] Batch[900] Loss[2.638] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[900] rmse=0.019399 lr=0.076643 +[1,0]:INFO:root:Epoch[193] Batch[1000] Loss[3.403] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[1000] rmse=0.019418 lr=0.076494 +[1,0]:INFO:root:Epoch[193] Batch[1100] Loss[2.616] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[1100] rmse=0.019415 lr=0.076345 +[1,0]:INFO:root:Epoch[193] Batch[1200] Loss[3.782] +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[1200] rmse=0.019404 lr=0.076196 +[1,0]:INFO:root:Epoch[193] Rank[0] Batch[1251] Time cost=398.90 Train-metric=0.019417 +[1,0]:INFO:root:Epoch[193] Speed: 3211.39 samples/sec +[1,0]:INFO:root:Epoch[194] Batch[100] Loss[4.145] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[100] rmse=0.019385 lr=0.075972 +[1,0]:INFO:root:Epoch[194] Batch[200] Loss[2.343] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[200] rmse=0.019352 lr=0.075823 +[1,0]:INFO:root:Epoch[194] Batch[300] Loss[2.595] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[300] rmse=0.019370 lr=0.075675 +[1,0]:INFO:root:Epoch[194] Batch[400] Loss[2.529] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[400] rmse=0.019392 lr=0.075527 +[1,0]:INFO:root:Epoch[194] Batch[500] Loss[2.564] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[500] rmse=0.019392 lr=0.075379 +[1,0]:INFO:root:Epoch[194] Batch[600] Loss[4.069] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[600] rmse=0.019422 lr=0.075231 +[1,0]:INFO:root:Epoch[194] Batch[700] Loss[3.533] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[700] rmse=0.019423 lr=0.075083 +[1,0]:INFO:root:Epoch[194] Batch[800] Loss[2.485] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[800] rmse=0.019427 lr=0.074935 +[1,0]:INFO:root:Epoch[194] Batch[900] Loss[2.507] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[900] rmse=0.019414 lr=0.074787 +[1,0]:INFO:root:Epoch[194] Batch[1000] Loss[2.988] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[1000] rmse=0.019424 lr=0.074639 +[1,0]:INFO:root:Epoch[194] Batch[1100] Loss[2.484] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[1100] rmse=0.019438 lr=0.074492 +[1,0]:INFO:root:Epoch[194] Batch[1200] Loss[3.202] +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[1200] rmse=0.019434 lr=0.074345 +[1,0]:INFO:root:Epoch[194] Rank[0] Batch[1251] Time cost=398.74 Train-metric=0.019440 +[1,0]:INFO:root:Epoch[194] Speed: 3212.65 samples/sec +[1,0]:INFO:root:Epoch[194] Rank[0] Validation-accuracy=0.694700 Validation-top_k_accuracy_5=0.894060 +[1,0]:INFO:root:Epoch[195] Batch[100] Loss[4.954] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[100] rmse=0.019319 lr=0.074122 +[1,0]:INFO:root:Epoch[195] Batch[200] Loss[2.335] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[200] rmse=0.019321 lr=0.073975 +[1,0]:INFO:root:Epoch[195] Batch[300] Loss[4.183] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[300] rmse=0.019301 lr=0.073828 +[1,0]:INFO:root:Epoch[195] Batch[400] Loss[2.412] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[400] rmse=0.019350 lr=0.073681 +[1,0]:INFO:root:Epoch[195] Batch[500] Loss[2.840] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[500] rmse=0.019338 lr=0.073534 +[1,0]:INFO:root:Epoch[195] Batch[600] Loss[2.473] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[600] rmse=0.019373 lr=0.073388 +[1,0]:INFO:root:Epoch[195] Batch[700] Loss[4.279] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[700] rmse=0.019376 lr=0.073241 +[1,0]:INFO:root:Epoch[195] Batch[800] Loss[3.362] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[800] rmse=0.019383 lr=0.073095 +[1,0]:INFO:root:Epoch[195] Batch[900] Loss[3.538] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[900] rmse=0.019384 lr=0.072948 +[1,0]:INFO:root:Epoch[195] Batch[1000] Loss[2.687] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[1000] rmse=0.019403 lr=0.072802 +[1,0]:INFO:root:Epoch[195] Batch[1100] Loss[2.312] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[1100] rmse=0.019407 lr=0.072656 +[1,0]:INFO:root:Epoch[195] Batch[1200] Loss[3.666] +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[1200] rmse=0.019412 lr=0.072510 +[1,0]:INFO:root:Epoch[195] Rank[0] Batch[1251] Time cost=398.65 Train-metric=0.019418 +[1,0]:INFO:root:Epoch[195] Speed: 3213.37 samples/sec +[1,0]:INFO:root:Epoch[196] Batch[100] Loss[2.546] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[100] rmse=0.019294 lr=0.072290 +[1,0]:INFO:root:Epoch[196] Batch[200] Loss[2.595] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[200] rmse=0.019302 lr=0.072144 +[1,0]:INFO:root:Epoch[196] Batch[300] Loss[2.867] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[300] rmse=0.019372 lr=0.071999 +[1,0]:INFO:root:Epoch[196] Batch[400] Loss[4.615] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[400] rmse=0.019343 lr=0.071853 +[1,0]:INFO:root:Epoch[196] Batch[500] Loss[2.675] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[500] rmse=0.019321 lr=0.071708 +[1,0]:INFO:root:Epoch[196] Batch[600] Loss[2.897] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[600] rmse=0.019333 lr=0.071563 +[1,0]:INFO:root:Epoch[196] Batch[700] Loss[3.235] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[700] rmse=0.019333 lr=0.071418 +[1,0]:INFO:root:Epoch[196] Batch[800] Loss[2.357] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[800] rmse=0.019326 lr=0.071273 +[1,0]:INFO:root:Epoch[196] Batch[900] Loss[2.816] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[900] rmse=0.019329 lr=0.071128 +[1,0]:INFO:root:Epoch[196] Batch[1000] Loss[2.453] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[1000] rmse=0.019339 lr=0.070983 +[1,0]:INFO:root:Epoch[196] Batch[1100] Loss[5.062] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[1100] rmse=0.019357 lr=0.070838 +[1,0]:INFO:root:Epoch[196] Batch[1200] Loss[2.772] +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[1200] rmse=0.019377 lr=0.070694 +[1,0]:INFO:root:Epoch[196] Rank[0] Batch[1251] Time cost=398.91 Train-metric=0.019373 +[1,0]:INFO:root:Epoch[196] Speed: 3211.31 samples/sec +[1,0]:INFO:root:Epoch[197] Batch[100] Loss[2.466] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[100] rmse=0.019284 lr=0.070476 +[1,0]:INFO:root:Epoch[197] Batch[200] Loss[3.091] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[200] rmse=0.019273 lr=0.070332 +[1,0]:INFO:root:Epoch[197] Batch[300] Loss[2.371] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[300] rmse=0.019286 lr=0.070187 +[1,0]:INFO:root:Epoch[197] Batch[400] Loss[4.283] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[400] rmse=0.019345 lr=0.070043 +[1,0]:INFO:root:Epoch[197] Batch[500] Loss[2.529] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[500] rmse=0.019329 lr=0.069900 +[1,0]:INFO:root:Epoch[197] Batch[600] Loss[2.731] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[600] rmse=0.019333 lr=0.069756 +[1,0]:INFO:root:Epoch[197] Batch[700] Loss[2.612] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[700] rmse=0.019332 lr=0.069612 +[1,0]:INFO:root:Epoch[197] Batch[800] Loss[3.058] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[800] rmse=0.019342 lr=0.069469 +[1,0]:INFO:root:Epoch[197] Batch[900] Loss[3.293] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[900] rmse=0.019331 lr=0.069325 +[1,0]:INFO:root:Epoch[197] Batch[1000] Loss[2.630] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[1000] rmse=0.019339 lr=0.069182 +[1,0]:INFO:root:Epoch[197] Batch[1100] Loss[4.400] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[1100] rmse=0.019346 lr=0.069039 +[1,0]:INFO:root:Epoch[197] Batch[1200] Loss[2.890] +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[1200] rmse=0.019334 lr=0.068896 +[1,0]:INFO:root:Epoch[197] Rank[0] Batch[1251] Time cost=399.07 Train-metric=0.019336 +[1,0]:INFO:root:Epoch[197] Speed: 3210.03 samples/sec +[1,0]:INFO:root:Epoch[198] Batch[100] Loss[4.309] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[100] rmse=0.019157 lr=0.068680 +[1,0]:INFO:root:Epoch[198] Batch[200] Loss[2.738] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[200] rmse=0.019191 lr=0.068537 +[1,0]:INFO:root:Epoch[198] Batch[300] Loss[2.336] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[300] rmse=0.019214 lr=0.068394 +[1,0]:INFO:root:Epoch[198] Batch[400] Loss[4.716] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[400] rmse=0.019225 lr=0.068252 +[1,0]:INFO:root:Epoch[198] Batch[500] Loss[2.717] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[500] rmse=0.019239 lr=0.068109 +[1,0]:INFO:root:Epoch[198] Batch[600] Loss[2.987] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[600] rmse=0.019267 lr=0.067967 +[1,0]:INFO:root:Epoch[198] Batch[700] Loss[2.111] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[700] rmse=0.019261 lr=0.067825 +[1,0]:INFO:root:Epoch[198] Batch[800] Loss[2.530] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[800] rmse=0.019284 lr=0.067683 +[1,0]:INFO:root:Epoch[198] Batch[900] Loss[3.174] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[900] rmse=0.019300 lr=0.067541 +[1,0]:INFO:root:Epoch[198] Batch[1000] Loss[3.435] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[1000] rmse=0.019317 lr=0.067399 +[1,0]:INFO:root:Epoch[198] Batch[1100] Loss[3.687] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[1100] rmse=0.019339 lr=0.067257 +[1,0]:INFO:root:Epoch[198] Batch[1200] Loss[2.418] +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[1200] rmse=0.019346 lr=0.067116 +[1,0]:INFO:root:Epoch[198] Rank[0] Batch[1251] Time cost=401.20 Train-metric=0.019339 +[1,0]:INFO:root:Epoch[198] Speed: 3193.02 samples/sec +[1,0]:INFO:root:Epoch[199] Batch[100] Loss[4.314] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[100] rmse=0.019321 lr=0.066902 +[1,0]:INFO:root:Epoch[199] Batch[200] Loss[2.261] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[200] rmse=0.019269 lr=0.066761 +[1,0]:INFO:root:Epoch[199] Batch[300] Loss[2.401] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[300] rmse=0.019262 lr=0.066620 +[1,0]:INFO:root:Epoch[199] Batch[400] Loss[3.011] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[400] rmse=0.019222 lr=0.066479 +[1,0]:INFO:root:Epoch[199] Batch[500] Loss[2.949] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[500] rmse=0.019225 lr=0.066338 +[1,0]:INFO:root:Epoch[199] Batch[600] Loss[2.534] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[600] rmse=0.019224 lr=0.066197 +[1,0]:INFO:root:Epoch[199] Batch[700] Loss[4.578] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[700] rmse=0.019243 lr=0.066056 +[1,0]:INFO:root:Epoch[199] Batch[800] Loss[2.554] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[800] rmse=0.019240 lr=0.065916 +[1,0]:INFO:root:Epoch[199] Batch[900] Loss[2.421] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[900] rmse=0.019253 lr=0.065775 +[1,0]:INFO:root:Epoch[199] Batch[1000] Loss[3.723] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[1000] rmse=0.019256 lr=0.065635 +[1,0]:INFO:root:Epoch[199] Batch[1100] Loss[3.081] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[1100] rmse=0.019267 lr=0.065495 +[1,0]:INFO:root:Epoch[199] Batch[1200] Loss[2.621] +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[1200] rmse=0.019271 lr=0.065355 +[1,0]:INFO:root:Epoch[199] Rank[0] Batch[1251] Time cost=401.49 Train-metric=0.019277 +[1,0]:INFO:root:Epoch[199] Speed: 3190.66 samples/sec +[1,0]:INFO:root:Epoch[199] Rank[0] Validation-accuracy=0.698140 Validation-top_k_accuracy_5=0.894400 +[1,0]:INFO:root:Epoch[200] Batch[100] Loss[3.660] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[100] rmse=0.019037 lr=0.065143 +[1,0]:INFO:root:Epoch[200] Batch[200] Loss[2.923] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[200] rmse=0.019170 lr=0.065003 +[1,0]:INFO:root:Epoch[200] Batch[300] Loss[4.595] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[300] rmse=0.019231 lr=0.064864 +[1,0]:INFO:root:Epoch[200] Batch[400] Loss[2.820] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[400] rmse=0.019229 lr=0.064724 +[1,0]:INFO:root:Epoch[200] Batch[500] Loss[2.583] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[500] rmse=0.019229 lr=0.064585 +[1,0]:INFO:root:Epoch[200] Batch[600] Loss[4.580] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[600] rmse=0.019247 lr=0.064445 +[1,0]:INFO:root:Epoch[200] Batch[700] Loss[2.668] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[700] rmse=0.019259 lr=0.064306 +[1,0]:INFO:root:Epoch[200] Batch[800] Loss[2.507] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[800] rmse=0.019246 lr=0.064167 +[1,0]:INFO:root:Epoch[200] Batch[900] Loss[2.769] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[900] rmse=0.019242 lr=0.064028 +[1,0]:INFO:root:Epoch[200] Batch[1000] Loss[2.520] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[1000] rmse=0.019236 lr=0.063889 +[1,0]:INFO:root:Epoch[200] Batch[1100] Loss[3.217] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[1100] rmse=0.019259 lr=0.063751 +[1,0]:INFO:root:Epoch[200] Batch[1200] Loss[2.475] +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[1200] rmse=0.019259 lr=0.063612 +[1,0]:INFO:root:Epoch[200] Rank[0] Batch[1251] Time cost=401.57 Train-metric=0.019256 +[1,0]:INFO:root:Epoch[200] Speed: 3190.02 samples/sec +[1,0]:INFO:root:Epoch[201] Batch[100] Loss[5.077] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[100] rmse=0.019120 lr=0.063403 +[1,0]:INFO:root:Epoch[201] Batch[200] Loss[2.344] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[200] rmse=0.019160 lr=0.063265 +[1,0]:INFO:root:Epoch[201] Batch[300] Loss[2.550] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[300] rmse=0.019141 lr=0.063127 +[1,0]:INFO:root:Epoch[201] Batch[400] Loss[3.036] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[400] rmse=0.019147 lr=0.062989 +[1,0]:INFO:root:Epoch[201] Batch[500] Loss[4.454] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[500] rmse=0.019158 lr=0.062851 +[1,0]:INFO:root:Epoch[201] Batch[600] Loss[5.054] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[600] rmse=0.019172 lr=0.062713 +[1,0]:INFO:root:Epoch[201] Batch[700] Loss[4.118] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[700] rmse=0.019181 lr=0.062575 +[1,0]:INFO:root:Epoch[201] Batch[800] Loss[2.780] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[800] rmse=0.019183 lr=0.062438 +[1,0]:INFO:root:Epoch[201] Batch[900] Loss[2.433] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[900] rmse=0.019196 lr=0.062300 +[1,0]:INFO:root:Epoch[201] Batch[1000] Loss[2.607] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[1000] rmse=0.019195 lr=0.062163 +[1,0]:INFO:root:Epoch[201] Batch[1100] Loss[2.214] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[1100] rmse=0.019196 lr=0.062026 +[1,0]:INFO:root:Epoch[201] Batch[1200] Loss[4.973] +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[1200] rmse=0.019191 lr=0.061889 +[1,0]:INFO:root:Epoch[201] Rank[0] Batch[1251] Time cost=403.37 Train-metric=0.019193 +[1,0]:INFO:root:Epoch[201] Speed: 3175.83 samples/sec +[1,0]:INFO:root:Epoch[202] Batch[100] Loss[4.071] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[100] rmse=0.019184 lr=0.061682 +[1,0]:INFO:root:Epoch[202] Batch[200] Loss[2.585] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[200] rmse=0.019200 lr=0.061546 +[1,0]:INFO:root:Epoch[202] Batch[300] Loss[3.013] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[300] rmse=0.019154 lr=0.061409 +[1,0]:INFO:root:Epoch[202] Batch[400] Loss[2.357] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[400] rmse=0.019171 lr=0.061273 +[1,0]:INFO:root:Epoch[202] Batch[500] Loss[4.812] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[500] rmse=0.019186 lr=0.061136 +[1,0]:INFO:root:Epoch[202] Batch[600] Loss[4.839] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[600] rmse=0.019181 lr=0.061000 +[1,0]:INFO:root:Epoch[202] Batch[700] Loss[4.511] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[700] rmse=0.019200 lr=0.060864 +[1,0]:INFO:root:Epoch[202] Batch[800] Loss[2.190] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[800] rmse=0.019200 lr=0.060728 +[1,0]:INFO:root:Epoch[202] Batch[900] Loss[2.742] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[900] rmse=0.019194 lr=0.060592 +[1,0]:INFO:root:Epoch[202] Batch[1000] Loss[2.703] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[1000] rmse=0.019199 lr=0.060456 +[1,0]:INFO:root:Epoch[202] Batch[1100] Loss[4.907] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[1100] rmse=0.019191 lr=0.060321 +[1,0]:INFO:root:Epoch[202] Batch[1200] Loss[4.531] +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[1200] rmse=0.019206 lr=0.060185 +[1,0]:INFO:root:Epoch[202] Rank[0] Batch[1251] Time cost=400.35 Train-metric=0.019205 +[1,0]:INFO:root:Epoch[202] Speed: 3199.75 samples/sec +[1,0]:INFO:root:Epoch[203] Batch[100] Loss[2.534] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[100] rmse=0.019040 lr=0.059981 +[1,0]:INFO:root:Epoch[203] Batch[200] Loss[2.482] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[200] rmse=0.019020 lr=0.059846 +[1,0]:INFO:root:Epoch[203] Batch[300] Loss[3.949] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[300] rmse=0.019026 lr=0.059711 +[1,0]:INFO:root:Epoch[203] Batch[400] Loss[2.579] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[400] rmse=0.019031 lr=0.059576 +[1,0]:INFO:root:Epoch[203] Batch[500] Loss[2.678] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[500] rmse=0.019046 lr=0.059441 +[1,0]:INFO:root:Epoch[203] Batch[600] Loss[2.784] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[600] rmse=0.019060 lr=0.059306 +[1,0]:INFO:root:Epoch[203] Batch[700] Loss[2.569] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[700] rmse=0.019076 lr=0.059172 +[1,0]:INFO:root:Epoch[203] Batch[800] Loss[3.587] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[800] rmse=0.019127 lr=0.059037 +[1,0]:INFO:root:Epoch[203] Batch[900] Loss[4.768] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[900] rmse=0.019140 lr=0.058903 +[1,0]:INFO:root:Epoch[203] Batch[1000] Loss[4.202] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[1000] rmse=0.019150 lr=0.058769 +[1,0]:INFO:root:Epoch[203] Batch[1100] Loss[5.072] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[1100] rmse=0.019153 lr=0.058635 +[1,0]:INFO:root:Epoch[203] Batch[1200] Loss[3.913] +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[1200] rmse=0.019166 lr=0.058501 +[1,0]:INFO:root:Epoch[203] Rank[0] Batch[1251] Time cost=399.99 Train-metric=0.019160 +[1,0]:INFO:root:Epoch[203] Speed: 3202.66 samples/sec +[1,0]:INFO:root:Epoch[204] Batch[100] Loss[2.009] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[100] rmse=0.018992 lr=0.058299 +[1,0]:INFO:root:Epoch[204] Batch[200] Loss[2.497] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[200] rmse=0.019015 lr=0.058165 +[1,0]:INFO:root:Epoch[204] Batch[300] Loss[2.446] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[300] rmse=0.019066 lr=0.058032 +[1,0]:INFO:root:Epoch[204] Batch[400] Loss[4.072] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[400] rmse=0.019108 lr=0.057899 +[1,0]:INFO:root:Epoch[204] Batch[500] Loss[2.659] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[500] rmse=0.019104 lr=0.057765 +[1,0]:INFO:root:Epoch[204] Batch[600] Loss[3.047] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[600] rmse=0.019124 lr=0.057632 +[1,0]:INFO:root:Epoch[204] Batch[700] Loss[2.808] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[700] rmse=0.019137 lr=0.057499 +[1,0]:INFO:root:Epoch[204] Batch[800] Loss[2.880] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[800] rmse=0.019138 lr=0.057367 +[1,0]:INFO:root:Epoch[204] Batch[900] Loss[2.547] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[900] rmse=0.019152 lr=0.057234 +[1,0]:INFO:root:Epoch[204] Batch[1000] Loss[3.037] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[1000] rmse=0.019151 lr=0.057101 +[1,0]:INFO:root:Epoch[204] Batch[1100] Loss[2.323] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[1100] rmse=0.019161 lr=0.056969 +[1,0]:INFO:root:Epoch[204] Batch[1200] Loss[2.647] +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[1200] rmse=0.019169 lr=0.056837 +[1,0]:INFO:root:Epoch[204] Rank[0] Batch[1251] Time cost=398.85 Train-metric=0.019168 +[1,0]:INFO:root:Epoch[204] Speed: 3211.82 samples/sec +[1,0]:INFO:root:Epoch[204] Rank[0] Validation-accuracy=0.702940 Validation-top_k_accuracy_5=0.898860 +[1,0]:INFO:root:Epoch[205] Batch[100] Loss[4.613] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[100] rmse=0.019023 lr=0.056637 +[1,0]:INFO:root:Epoch[205] Batch[200] Loss[3.752] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[200] rmse=0.019057 lr=0.056505 +[1,0]:INFO:root:Epoch[205] Batch[300] Loss[3.026] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[300] rmse=0.019050 lr=0.056373 +[1,0]:INFO:root:Epoch[205] Batch[400] Loss[4.325] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[400] rmse=0.019037 lr=0.056242 +[1,0]:INFO:root:Epoch[205] Batch[500] Loss[3.576] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[500] rmse=0.019024 lr=0.056110 +[1,0]:INFO:root:Epoch[205] Batch[600] Loss[2.414] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[600] rmse=0.019029 lr=0.055979 +[1,0]:INFO:root:Epoch[205] Batch[700] Loss[2.709] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[700] rmse=0.019038 lr=0.055847 +[1,0]:INFO:root:Epoch[205] Batch[800] Loss[4.025] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[800] rmse=0.019066 lr=0.055716 +[1,0]:INFO:root:Epoch[205] Batch[900] Loss[4.236] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[900] rmse=0.019064 lr=0.055585 +[1,0]:INFO:root:Epoch[205] Batch[1000] Loss[2.516] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[1000] rmse=0.019088 lr=0.055454 +[1,0]:INFO:root:Epoch[205] Batch[1100] Loss[4.850] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[1100] rmse=0.019100 lr=0.055323 +[1,0]:INFO:root:Epoch[205] Batch[1200] Loss[2.387] +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[1200] rmse=0.019108 lr=0.055192 +[1,0]:INFO:root:Epoch[205] Rank[0] Batch[1251] Time cost=398.60 Train-metric=0.019105 +[1,0]:INFO:root:Epoch[205] Speed: 3213.79 samples/sec +[1,0]:INFO:root:Epoch[206] Batch[100] Loss[2.559] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[100] rmse=0.019131 lr=0.054995 +[1,0]:INFO:root:Epoch[206] Batch[200] Loss[3.618] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[200] rmse=0.019129 lr=0.054865 +[1,0]:INFO:root:Epoch[206] Batch[300] Loss[2.651] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[300] rmse=0.019152 lr=0.054735 +[1,0]:INFO:root:Epoch[206] Batch[400] Loss[4.035] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[400] rmse=0.019132 lr=0.054605 +[1,0]:INFO:root:Epoch[206] Batch[500] Loss[3.025] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[500] rmse=0.019101 lr=0.054475 +[1,0]:INFO:root:Epoch[206] Batch[600] Loss[2.491] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[600] rmse=0.019095 lr=0.054345 +[1,0]:INFO:root:Epoch[206] Batch[700] Loss[2.475] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[700] rmse=0.019090 lr=0.054215 +[1,0]:INFO:root:Epoch[206] Batch[800] Loss[2.530] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[800] rmse=0.019093 lr=0.054086 +[1,0]:INFO:root:Epoch[206] Batch[900] Loss[2.591] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[900] rmse=0.019088 lr=0.053956 +[1,0]:INFO:root:Epoch[206] Batch[1000] Loss[2.541] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[1000] rmse=0.019091 lr=0.053827 +[1,0]:INFO:root:Epoch[206] Batch[1100] Loss[2.920] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[1100] rmse=0.019096 lr=0.053698 +[1,0]:INFO:root:Epoch[206] Batch[1200] Loss[2.320] +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[1200] rmse=0.019108 lr=0.053568 +[1,0]:INFO:root:Epoch[206] Rank[0] Batch[1251] Time cost=398.41 Train-metric=0.019105 +[1,0]:INFO:root:Epoch[206] Speed: 3215.32 samples/sec +[1,0]:INFO:root:Epoch[207] Batch[100] Loss[2.685] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[100] rmse=0.019015 lr=0.053374 +[1,0]:INFO:root:Epoch[207] Batch[200] Loss[2.963] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[200] rmse=0.019043 lr=0.053245 +[1,0]:INFO:root:Epoch[207] Batch[300] Loss[2.579] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[300] rmse=0.019063 lr=0.053117 +[1,0]:INFO:root:Epoch[207] Batch[400] Loss[2.565] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[400] rmse=0.019053 lr=0.052988 +[1,0]:INFO:root:Epoch[207] Batch[500] Loss[2.256] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[500] rmse=0.019055 lr=0.052860 +[1,0]:INFO:root:Epoch[207] Batch[600] Loss[2.415] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[600] rmse=0.019035 lr=0.052732 +[1,0]:INFO:root:Epoch[207] Batch[700] Loss[2.555] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[700] rmse=0.019043 lr=0.052603 +[1,0]:INFO:root:Epoch[207] Batch[800] Loss[4.473] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[800] rmse=0.019050 lr=0.052476 +[1,0]:INFO:root:Epoch[207] Batch[900] Loss[4.691] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[900] rmse=0.019053 lr=0.052348 +[1,0]:INFO:root:Epoch[207] Batch[1000] Loss[2.247] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[1000] rmse=0.019051 lr=0.052220 +[1,0]:INFO:root:Epoch[207] Batch[1100] Loss[2.920] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[1100] rmse=0.019061 lr=0.052093 +[1,0]:INFO:root:Epoch[207] Batch[1200] Loss[2.460] +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[1200] rmse=0.019070 lr=0.051965 +[1,0]:INFO:root:Epoch[207] Rank[0] Batch[1251] Time cost=398.95 Train-metric=0.019075 +[1,0]:INFO:root:Epoch[207] Speed: 3210.97 samples/sec +[1,0]:INFO:root:Epoch[208] Batch[100] Loss[2.392] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[100] rmse=0.018859 lr=0.051773 +[1,0]:INFO:root:Epoch[208] Batch[200] Loss[2.609] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[200] rmse=0.018918 lr=0.051646 +[1,0]:INFO:root:Epoch[208] Batch[300] Loss[2.668] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[300] rmse=0.018993 lr=0.051519 +[1,0]:INFO:root:Epoch[208] Batch[400] Loss[2.062] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[400] rmse=0.019008 lr=0.051392 +[1,0]:INFO:root:Epoch[208] Batch[500] Loss[2.659] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[500] rmse=0.019064 lr=0.051265 +[1,0]:INFO:root:Epoch[208] Batch[600] Loss[3.645] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[600] rmse=0.019068 lr=0.051139 +[1,0]:INFO:root:Epoch[208] Batch[700] Loss[2.408] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[700] rmse=0.019063 lr=0.051013 +[1,0]:INFO:root:Epoch[208] Batch[800] Loss[2.772] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[800] rmse=0.019076 lr=0.050886 +[1,0]:INFO:root:Epoch[208] Batch[900] Loss[4.364] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[900] rmse=0.019075 lr=0.050760 +[1,0]:INFO:root:Epoch[208] Batch[1000] Loss[2.616] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[1000] rmse=0.019079 lr=0.050634 +[1,0]:INFO:root:Epoch[208] Batch[1100] Loss[2.204] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[1100] rmse=0.019077 lr=0.050508 +[1,0]:INFO:root:Epoch[208] Batch[1200] Loss[4.946] +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[1200] rmse=0.019073 lr=0.050383 +[1,0]:INFO:root:Epoch[208] Rank[0] Batch[1251] Time cost=399.34 Train-metric=0.019069 +[1,0]:INFO:root:Epoch[208] Speed: 3207.85 samples/sec +[1,0]:INFO:root:Epoch[209] Batch[100] Loss[3.771] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[100] rmse=0.018878 lr=0.050193 +[1,0]:INFO:root:Epoch[209] Batch[200] Loss[2.349] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[200] rmse=0.018892 lr=0.050067 +[1,0]:INFO:root:Epoch[209] Batch[300] Loss[2.568] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[300] rmse=0.018921 lr=0.049942 +[1,0]:INFO:root:Epoch[209] Batch[400] Loss[2.784] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[400] rmse=0.018904 lr=0.049817 +[1,0]:INFO:root:Epoch[209] Batch[500] Loss[2.236] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[500] rmse=0.018917 lr=0.049692 +[1,0]:INFO:root:Epoch[209] Batch[600] Loss[4.509] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[600] rmse=0.018939 lr=0.049567 +[1,0]:INFO:root:Epoch[209] Batch[700] Loss[2.739] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[700] rmse=0.018947 lr=0.049443 +[1,0]:INFO:root:Epoch[209] Batch[800] Loss[3.449] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[800] rmse=0.018971 lr=0.049318 +[1,0]:INFO:root:Epoch[209] Batch[900] Loss[2.229] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[900] rmse=0.018979 lr=0.049193 +[1,0]:INFO:root:Epoch[209] Batch[1000] Loss[2.527] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[1000] rmse=0.018992 lr=0.049069 +[1,0]:INFO:root:Epoch[209] Batch[1100] Loss[4.521] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[1100] rmse=0.019002 lr=0.048945 +[1,0]:INFO:root:Epoch[209] Batch[1200] Loss[2.436] +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[1200] rmse=0.019001 lr=0.048821 +[1,0]:INFO:root:Epoch[209] Rank[0] Batch[1251] Time cost=399.51 Train-metric=0.019016 +[1,0]:INFO:root:Epoch[209] Speed: 3206.47 samples/sec +[1,0]:INFO:root:Epoch[209] Rank[0] Validation-accuracy=0.711000 Validation-top_k_accuracy_5=0.902380 +[1,0]:INFO:root:Epoch[210] Batch[100] Loss[4.221] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[100] rmse=0.018878 lr=0.048634 +[1,0]:INFO:root:Epoch[210] Batch[200] Loss[2.171] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[200] rmse=0.018900 lr=0.048510 +[1,0]:INFO:root:Epoch[210] Batch[300] Loss[2.783] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[300] rmse=0.018893 lr=0.048387 +[1,0]:INFO:root:Epoch[210] Batch[400] Loss[2.627] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[400] rmse=0.018923 lr=0.048263 +[1,0]:INFO:root:Epoch[210] Batch[500] Loss[2.743] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[500] rmse=0.018950 lr=0.048140 +[1,0]:INFO:root:Epoch[210] Batch[600] Loss[2.319] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[600] rmse=0.018975 lr=0.048017 +[1,0]:INFO:root:Epoch[210] Batch[700] Loss[2.292] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[700] rmse=0.019000 lr=0.047894 +[1,0]:INFO:root:Epoch[210] Batch[800] Loss[4.869] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[800] rmse=0.018993 lr=0.047771 +[1,0]:INFO:root:Epoch[210] Batch[900] Loss[2.514] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[900] rmse=0.018995 lr=0.047648 +[1,0]:INFO:root:Epoch[210] Batch[1000] Loss[4.834] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[1000] rmse=0.019011 lr=0.047525 +[1,0]:INFO:root:Epoch[210] Batch[1100] Loss[2.560] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[1100] rmse=0.019011 lr=0.047403 +[1,0]:INFO:root:Epoch[210] Batch[1200] Loss[2.788] +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[1200] rmse=0.019027 lr=0.047280 +[1,0]:INFO:root:Epoch[210] Rank[0] Batch[1251] Time cost=413.22 Train-metric=0.019029 +[1,0]:INFO:root:Epoch[210] Speed: 3100.08 samples/sec +[1,0]:INFO:root:Epoch[211] Batch[100] Loss[2.480] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[100] rmse=0.018746 lr=0.047096 +[1,0]:INFO:root:Epoch[211] Batch[200] Loss[2.574] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[200] rmse=0.018833 lr=0.046974 +[1,0]:INFO:root:Epoch[211] Batch[300] Loss[2.250] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[300] rmse=0.018877 lr=0.046852 +[1,0]:INFO:root:Epoch[211] Batch[400] Loss[5.086] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[400] rmse=0.018873 lr=0.046730 +[1,0]:INFO:root:Epoch[211] Batch[500] Loss[3.953] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[500] rmse=0.018869 lr=0.046609 +[1,0]:INFO:root:Epoch[211] Batch[600] Loss[2.175] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[600] rmse=0.018879 lr=0.046487 +[1,0]:INFO:root:Epoch[211] Batch[700] Loss[5.018] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[700] rmse=0.018885 lr=0.046366 +[1,0]:INFO:root:Epoch[211] Batch[800] Loss[2.366] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[800] rmse=0.018909 lr=0.046245 +[1,0]:INFO:root:Epoch[211] Batch[900] Loss[4.290] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[900] rmse=0.018917 lr=0.046124 +[1,0]:INFO:root:Epoch[211] Batch[1000] Loss[2.360] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[1000] rmse=0.018923 lr=0.046003 +[1,0]:INFO:root:Epoch[211] Batch[1100] Loss[4.552] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[1100] rmse=0.018928 lr=0.045882 +[1,0]:INFO:root:Epoch[211] Batch[1200] Loss[2.790] +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[1200] rmse=0.018929 lr=0.045762 +[1,0]:INFO:root:Epoch[211] Rank[0] Batch[1251] Time cost=400.01 Train-metric=0.018940 +[1,0]:INFO:root:Epoch[211] Speed: 3202.46 samples/sec +[1,0]:INFO:root:Epoch[212] Batch[100] Loss[3.054] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[100] rmse=0.018807 lr=0.045580 +[1,0]:INFO:root:Epoch[212] Batch[200] Loss[2.342] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[200] rmse=0.018833 lr=0.045459 +[1,0]:INFO:root:Epoch[212] Batch[300] Loss[3.573] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[300] rmse=0.018843 lr=0.045339 +[1,0]:INFO:root:Epoch[212] Batch[400] Loss[4.786] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[400] rmse=0.018900 lr=0.045219 +[1,0]:INFO:root:Epoch[212] Batch[500] Loss[4.406] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[500] rmse=0.018918 lr=0.045099 +[1,0]:INFO:root:Epoch[212] Batch[600] Loss[2.388] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[600] rmse=0.018940 lr=0.044980 +[1,0]:INFO:root:Epoch[212] Batch[700] Loss[3.410] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[700] rmse=0.018931 lr=0.044860 +[1,0]:INFO:root:Epoch[212] Batch[800] Loss[4.162] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[800] rmse=0.018938 lr=0.044741 +[1,0]:INFO:root:Epoch[212] Batch[900] Loss[2.806] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[900] rmse=0.018940 lr=0.044621 +[1,0]:INFO:root:Epoch[212] Batch[1000] Loss[2.431] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[1000] rmse=0.018931 lr=0.044502 +[1,0]:INFO:root:Epoch[212] Batch[1100] Loss[2.635] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[1100] rmse=0.018931 lr=0.044383 +[1,0]:INFO:root:Epoch[212] Batch[1200] Loss[3.911] +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[1200] rmse=0.018933 lr=0.044264 +[1,0]:INFO:root:Epoch[212] Rank[0] Batch[1251] Time cost=399.09 Train-metric=0.018931 +[1,0]:INFO:root:Epoch[212] Speed: 3209.84 samples/sec +[1,0]:INFO:root:Epoch[213] Batch[100] Loss[2.937] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[100] rmse=0.018873 lr=0.044085 +[1,0]:INFO:root:Epoch[213] Batch[200] Loss[5.110] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[200] rmse=0.018819 lr=0.043966 +[1,0]:INFO:root:Epoch[213] Batch[300] Loss[2.479] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[300] rmse=0.018812 lr=0.043848 +[1,0]:INFO:root:Epoch[213] Batch[400] Loss[3.732] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[400] rmse=0.018812 lr=0.043730 +[1,0]:INFO:root:Epoch[213] Batch[500] Loss[2.553] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[500] rmse=0.018833 lr=0.043612 +[1,0]:INFO:root:Epoch[213] Batch[600] Loss[3.374] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[600] rmse=0.018847 lr=0.043494 +[1,0]:INFO:root:Epoch[213] Batch[700] Loss[4.163] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[700] rmse=0.018842 lr=0.043376 +[1,0]:INFO:root:Epoch[213] Batch[800] Loss[2.677] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[800] rmse=0.018851 lr=0.043258 +[1,0]:INFO:root:Epoch[213] Batch[900] Loss[3.478] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[900] rmse=0.018854 lr=0.043141 +[1,0]:INFO:root:Epoch[213] Batch[1000] Loss[2.510] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[1000] rmse=0.018885 lr=0.043023 +[1,0]:INFO:root:Epoch[213] Batch[1100] Loss[2.637] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[1100] rmse=0.018881 lr=0.042906 +[1,0]:INFO:root:Epoch[213] Batch[1200] Loss[4.795] +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[1200] rmse=0.018886 lr=0.042789 +[1,0]:INFO:root:Epoch[213] Rank[0] Batch[1251] Time cost=399.52 Train-metric=0.018890 +[1,0]:INFO:root:Epoch[213] Speed: 3206.40 samples/sec +[1,0]:INFO:root:Epoch[214] Batch[100] Loss[2.960] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[100] rmse=0.018789 lr=0.042612 +[1,0]:INFO:root:Epoch[214] Batch[200] Loss[2.231] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[200] rmse=0.018736 lr=0.042495 +[1,0]:INFO:root:Epoch[214] Batch[300] Loss[4.058] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[300] rmse=0.018857 lr=0.042379 +[1,0]:INFO:root:Epoch[214] Batch[400] Loss[2.409] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[400] rmse=0.018847 lr=0.042262 +[1,0]:INFO:root:Epoch[214] Batch[500] Loss[2.238] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[500] rmse=0.018806 lr=0.042146 +[1,0]:INFO:root:Epoch[214] Batch[600] Loss[2.547] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[600] rmse=0.018824 lr=0.042030 +[1,0]:INFO:root:Epoch[214] Batch[700] Loss[2.415] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[700] rmse=0.018812 lr=0.041914 +[1,0]:INFO:root:Epoch[214] Batch[800] Loss[2.924] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[800] rmse=0.018815 lr=0.041798 +[1,0]:INFO:root:Epoch[214] Batch[900] Loss[2.308] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[900] rmse=0.018806 lr=0.041682 +[1,0]:INFO:root:Epoch[214] Batch[1000] Loss[2.437] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[1000] rmse=0.018813 lr=0.041566 +[1,0]:INFO:root:Epoch[214] Batch[1100] Loss[3.914] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[1100] rmse=0.018820 lr=0.041451 +[1,0]:INFO:root:Epoch[214] Batch[1200] Loss[2.589] +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[1200] rmse=0.018816 lr=0.041335 +[1,0]:INFO:root:Epoch[214] Rank[0] Batch[1251] Time cost=399.01 Train-metric=0.018829 +[1,0]:INFO:root:Epoch[214] Speed: 3210.52 samples/sec +[1,0]:INFO:root:Epoch[214] Rank[0] Validation-accuracy=0.714180 Validation-top_k_accuracy_5=0.902960 +[1,0]:INFO:root:Epoch[215] Batch[100] Loss[2.410] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[100] rmse=0.018812 lr=0.041161 +[1,0]:INFO:root:Epoch[215] Batch[200] Loss[3.049] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[200] rmse=0.018798 lr=0.041046 +[1,0]:INFO:root:Epoch[215] Batch[300] Loss[2.542] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[300] rmse=0.018792 lr=0.040931 +[1,0]:INFO:root:Epoch[215] Batch[400] Loss[4.849] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[400] rmse=0.018767 lr=0.040817 +[1,0]:INFO:root:Epoch[215] Batch[500] Loss[2.347] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[500] rmse=0.018790 lr=0.040702 +[1,0]:INFO:root:Epoch[215] Batch[600] Loss[2.391] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[600] rmse=0.018795 lr=0.040588 +[1,0]:INFO:root:Epoch[215] Batch[700] Loss[2.351] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[700] rmse=0.018811 lr=0.040473 +[1,0]:INFO:root:Epoch[215] Batch[800] Loss[2.467] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[800] rmse=0.018808 lr=0.040359 +[1,0]:INFO:root:Epoch[215] Batch[900] Loss[2.492] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[900] rmse=0.018805 lr=0.040245 +[1,0]:INFO:root:Epoch[215] Batch[1000] Loss[2.965] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[1000] rmse=0.018814 lr=0.040131 +[1,0]:INFO:root:Epoch[215] Batch[1100] Loss[3.447] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[1100] rmse=0.018812 lr=0.040018 +[1,0]:INFO:root:Epoch[215] Batch[1200] Loss[4.862] +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[1200] rmse=0.018819 lr=0.039904 +[1,0]:INFO:root:Epoch[215] Rank[0] Batch[1251] Time cost=398.32 Train-metric=0.018827 +[1,0]:INFO:root:Epoch[215] Speed: 3216.06 samples/sec +[1,0]:INFO:root:Epoch[216] Batch[100] Loss[4.603] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[100] rmse=0.018644 lr=0.039733 +[1,0]:INFO:root:Epoch[216] Batch[200] Loss[2.370] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[200] rmse=0.018657 lr=0.039620 +[1,0]:INFO:root:Epoch[216] Batch[300] Loss[2.264] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[300] rmse=0.018677 lr=0.039507 +[1,0]:INFO:root:Epoch[216] Batch[400] Loss[2.876] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[400] rmse=0.018743 lr=0.039394 +[1,0]:INFO:root:Epoch[216] Batch[500] Loss[4.250] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[500] rmse=0.018758 lr=0.039281 +[1,0]:INFO:root:Epoch[216] Batch[600] Loss[2.320] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[600] rmse=0.018773 lr=0.039168 +[1,0]:INFO:root:Epoch[216] Batch[700] Loss[3.586] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[700] rmse=0.018762 lr=0.039056 +[1,0]:INFO:root:Epoch[216] Batch[800] Loss[2.403] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[800] rmse=0.018765 lr=0.038943 +[1,0]:INFO:root:Epoch[216] Batch[900] Loss[3.370] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[900] rmse=0.018786 lr=0.038831 +[1,0]:INFO:root:Epoch[216] Batch[1000] Loss[2.448] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[1000] rmse=0.018781 lr=0.038719 +[1,0]:INFO:root:Epoch[216] Batch[1100] Loss[2.539] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[1100] rmse=0.018778 lr=0.038607 +[1,0]:INFO:root:Epoch[216] Batch[1200] Loss[2.407] +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[1200] rmse=0.018784 lr=0.038495 +[1,0]:INFO:root:Epoch[216] Rank[0] Batch[1251] Time cost=398.81 Train-metric=0.018779 +[1,0]:INFO:root:Epoch[216] Speed: 3212.14 samples/sec +[1,0]:INFO:root:Epoch[217] Batch[100] Loss[2.352] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[100] rmse=0.018843 lr=0.038327 +[1,0]:INFO:root:Epoch[217] Batch[200] Loss[4.636] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[200] rmse=0.018767 lr=0.038216 +[1,0]:INFO:root:Epoch[217] Batch[300] Loss[2.307] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[300] rmse=0.018808 lr=0.038104 +[1,0]:INFO:root:Epoch[217] Batch[400] Loss[2.378] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[400] rmse=0.018801 lr=0.037993 +[1,0]:INFO:root:Epoch[217] Batch[500] Loss[2.729] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[500] rmse=0.018773 lr=0.037882 +[1,0]:INFO:root:Epoch[217] Batch[600] Loss[2.686] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[600] rmse=0.018755 lr=0.037771 +[1,0]:INFO:root:Epoch[217] Batch[700] Loss[2.550] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[700] rmse=0.018756 lr=0.037661 +[1,0]:INFO:root:Epoch[217] Batch[800] Loss[2.190] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[800] rmse=0.018763 lr=0.037550 +[1,0]:INFO:root:Epoch[217] Batch[900] Loss[2.743] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[900] rmse=0.018770 lr=0.037440 +[1,0]:INFO:root:Epoch[217] Batch[1000] Loss[2.368] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[1000] rmse=0.018761 lr=0.037329 +[1,0]:INFO:root:Epoch[217] Batch[1100] Loss[5.036] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[1100] rmse=0.018763 lr=0.037219 +[1,0]:INFO:root:Epoch[217] Batch[1200] Loss[2.303] +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[1200] rmse=0.018778 lr=0.037109 +[1,0]:INFO:root:Epoch[217] Rank[0] Batch[1251] Time cost=399.67 Train-metric=0.018780 +[1,0]:INFO:root:Epoch[217] Speed: 3205.24 samples/sec +[1,0]:INFO:root:Epoch[218] Batch[100] Loss[2.316] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[100] rmse=0.018654 lr=0.036944 +[1,0]:INFO:root:Epoch[218] Batch[200] Loss[3.415] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[200] rmse=0.018691 lr=0.036834 +[1,0]:INFO:root:Epoch[218] Batch[300] Loss[3.525] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[300] rmse=0.018691 lr=0.036725 +[1,0]:INFO:root:Epoch[218] Batch[400] Loss[2.207] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[400] rmse=0.018705 lr=0.036615 +[1,0]:INFO:root:Epoch[218] Batch[500] Loss[2.664] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[500] rmse=0.018717 lr=0.036506 +[1,0]:INFO:root:Epoch[218] Batch[600] Loss[2.950] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[600] rmse=0.018721 lr=0.036397 +[1,0]:INFO:root:Epoch[218] Batch[700] Loss[2.517] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[700] rmse=0.018725 lr=0.036288 +[1,0]:INFO:root:Epoch[218] Batch[800] Loss[2.427] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[800] rmse=0.018736 lr=0.036180 +[1,0]:INFO:root:Epoch[218] Batch[900] Loss[2.469] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[900] rmse=0.018745 lr=0.036071 +[1,0]:INFO:root:Epoch[218] Batch[1000] Loss[2.339] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[1000] rmse=0.018754 lr=0.035963 +[1,0]:INFO:root:Epoch[218] Batch[1100] Loss[2.251] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[1100] rmse=0.018763 lr=0.035854 +[1,0]:INFO:root:Epoch[218] Batch[1200] Loss[2.343] +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[1200] rmse=0.018769 lr=0.035746 +[1,0]:INFO:root:Epoch[218] Rank[0] Batch[1251] Time cost=398.72 Train-metric=0.018765 +[1,0]:INFO:root:Epoch[218] Speed: 3212.81 samples/sec +[1,0]:INFO:root:Epoch[219] Batch[100] Loss[4.922] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[100] rmse=0.018665 lr=0.035583 +[1,0]:INFO:root:Epoch[219] Batch[200] Loss[2.223] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[200] rmse=0.018693 lr=0.035476 +[1,0]:INFO:root:Epoch[219] Batch[300] Loss[3.424] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[300] rmse=0.018679 lr=0.035368 +[1,0]:INFO:root:Epoch[219] Batch[400] Loss[2.113] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[400] rmse=0.018698 lr=0.035260 +[1,0]:INFO:root:Epoch[219] Batch[500] Loss[2.137] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[500] rmse=0.018669 lr=0.035153 +[1,0]:INFO:root:Epoch[219] Batch[600] Loss[3.436] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[600] rmse=0.018692 lr=0.035046 +[1,0]:INFO:root:Epoch[219] Batch[700] Loss[2.354] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[700] rmse=0.018685 lr=0.034939 +[1,0]:INFO:root:Epoch[219] Batch[800] Loss[2.111] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[800] rmse=0.018675 lr=0.034832 +[1,0]:INFO:root:Epoch[219] Batch[900] Loss[4.927] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[900] rmse=0.018685 lr=0.034725 +[1,0]:INFO:root:Epoch[219] Batch[1000] Loss[2.469] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[1000] rmse=0.018684 lr=0.034619 +[1,0]:INFO:root:Epoch[219] Batch[1100] Loss[4.399] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[1100] rmse=0.018701 lr=0.034512 +[1,0]:INFO:root:Epoch[219] Batch[1200] Loss[2.396] +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[1200] rmse=0.018701 lr=0.034406 +[1,0]:INFO:root:Epoch[219] Rank[0] Batch[1251] Time cost=399.47 Train-metric=0.018701 +[1,0]:INFO:root:Epoch[219] Speed: 3206.82 samples/sec +[1,0]:INFO:root:Epoch[219] Rank[0] Validation-accuracy=0.719280 Validation-top_k_accuracy_5=0.905940 +[1,0]:INFO:root:Epoch[220] Batch[100] Loss[2.534] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[100] rmse=0.018389 lr=0.034246 +[1,0]:INFO:root:Epoch[220] Batch[200] Loss[4.317] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[200] rmse=0.018540 lr=0.034140 +[1,0]:INFO:root:Epoch[220] Batch[300] Loss[2.282] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[300] rmse=0.018579 lr=0.034034 +[1,0]:INFO:root:Epoch[220] Batch[400] Loss[2.062] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[400] rmse=0.018575 lr=0.033929 +[1,0]:INFO:root:Epoch[220] Batch[500] Loss[4.439] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[500] rmse=0.018587 lr=0.033823 +[1,0]:INFO:root:Epoch[220] Batch[600] Loss[3.135] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[600] rmse=0.018601 lr=0.033718 +[1,0]:INFO:root:Epoch[220] Batch[700] Loss[4.665] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[700] rmse=0.018613 lr=0.033613 +[1,0]:INFO:root:Epoch[220] Batch[800] Loss[3.517] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[800] rmse=0.018634 lr=0.033508 +[1,0]:INFO:root:Epoch[220] Batch[900] Loss[2.455] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[900] rmse=0.018646 lr=0.033403 +[1,0]:INFO:root:Epoch[220] Batch[1000] Loss[4.268] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[1000] rmse=0.018650 lr=0.033298 +[1,0]:INFO:root:Epoch[220] Batch[1100] Loss[2.637] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[1100] rmse=0.018654 lr=0.033194 +[1,0]:INFO:root:Epoch[220] Batch[1200] Loss[2.337] +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[1200] rmse=0.018662 lr=0.033089 +[1,0]:INFO:root:Epoch[220] Rank[0] Batch[1251] Time cost=397.31 Train-metric=0.018666 +[1,0]:INFO:root:Epoch[220] Speed: 3224.26 samples/sec +[1,0]:INFO:root:Epoch[221] Batch[100] Loss[3.883] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[100] rmse=0.018498 lr=0.032932 +[1,0]:INFO:root:Epoch[221] Batch[200] Loss[2.502] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[200] rmse=0.018516 lr=0.032828 +[1,0]:INFO:root:Epoch[221] Batch[300] Loss[3.286] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[300] rmse=0.018503 lr=0.032724 +[1,0]:INFO:root:Epoch[221] Batch[400] Loss[2.308] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[400] rmse=0.018569 lr=0.032620 +[1,0]:INFO:root:Epoch[221] Batch[500] Loss[2.304] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[500] rmse=0.018589 lr=0.032517 +[1,0]:INFO:root:Epoch[221] Batch[600] Loss[3.123] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[600] rmse=0.018584 lr=0.032413 +[1,0]:INFO:root:Epoch[221] Batch[700] Loss[3.001] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[700] rmse=0.018577 lr=0.032310 +[1,0]:INFO:root:Epoch[221] Batch[800] Loss[4.645] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[800] rmse=0.018578 lr=0.032207 +[1,0]:INFO:root:Epoch[221] Batch[900] Loss[2.455] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[900] rmse=0.018584 lr=0.032104 +[1,0]:INFO:root:Epoch[221] Batch[1000] Loss[2.459] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[1000] rmse=0.018595 lr=0.032001 +[1,0]:INFO:root:Epoch[221] Batch[1100] Loss[2.720] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[1100] rmse=0.018602 lr=0.031898 +[1,0]:INFO:root:Epoch[221] Batch[1200] Loss[2.302] +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[1200] rmse=0.018618 lr=0.031796 +[1,0]:INFO:root:Epoch[221] Rank[0] Batch[1251] Time cost=399.24 Train-metric=0.018615 +[1,0]:INFO:root:Epoch[221] Speed: 3208.62 samples/sec +[1,0]:INFO:root:Epoch[222] Batch[100] Loss[2.204] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[100] rmse=0.018551 lr=0.031641 +[1,0]:INFO:root:Epoch[222] Batch[200] Loss[3.333] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[200] rmse=0.018520 lr=0.031539 +[1,0]:INFO:root:Epoch[222] Batch[300] Loss[3.352] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[300] rmse=0.018539 lr=0.031437 +[1,0]:INFO:root:Epoch[222] Batch[400] Loss[2.037] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[400] rmse=0.018539 lr=0.031335 +[1,0]:INFO:root:Epoch[222] Batch[500] Loss[4.405] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[500] rmse=0.018536 lr=0.031234 +[1,0]:INFO:root:Epoch[222] Batch[600] Loss[4.667] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[600] rmse=0.018541 lr=0.031132 +[1,0]:INFO:root:Epoch[222] Batch[700] Loss[2.595] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[700] rmse=0.018519 lr=0.031031 +[1,0]:INFO:root:Epoch[222] Batch[800] Loss[4.149] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[800] rmse=0.018552 lr=0.030929 +[1,0]:INFO:root:Epoch[222] Batch[900] Loss[2.503] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[900] rmse=0.018558 lr=0.030828 +[1,0]:INFO:root:Epoch[222] Batch[1000] Loss[2.612] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[1000] rmse=0.018580 lr=0.030727 +[1,0]:INFO:root:Epoch[222] Batch[1100] Loss[2.208] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[1100] rmse=0.018584 lr=0.030627 +[1,0]:INFO:root:Epoch[222] Batch[1200] Loss[4.722] +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[1200] rmse=0.018592 lr=0.030526 +[1,0]:INFO:root:Epoch[222] Rank[0] Batch[1251] Time cost=399.50 Train-metric=0.018590 +[1,0]:INFO:root:Epoch[222] Speed: 3206.55 samples/sec +[1,0]:INFO:root:Epoch[223] Batch[100] Loss[2.617] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[100] rmse=0.018343 lr=0.030374 +[1,0]:INFO:root:Epoch[223] Batch[200] Loss[2.803] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[200] rmse=0.018509 lr=0.030274 +[1,0]:INFO:root:Epoch[223] Batch[300] Loss[2.575] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[300] rmse=0.018451 lr=0.030174 +[1,0]:INFO:root:Epoch[223] Batch[400] Loss[2.276] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[400] rmse=0.018456 lr=0.030074 +[1,0]:INFO:root:Epoch[223] Batch[500] Loss[4.923] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[500] rmse=0.018464 lr=0.029974 +[1,0]:INFO:root:Epoch[223] Batch[600] Loss[2.417] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[600] rmse=0.018483 lr=0.029874 +[1,0]:INFO:root:Epoch[223] Batch[700] Loss[2.334] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[700] rmse=0.018506 lr=0.029775 +[1,0]:INFO:root:Epoch[223] Batch[800] Loss[4.293] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[800] rmse=0.018500 lr=0.029676 +[1,0]:INFO:root:Epoch[223] Batch[900] Loss[2.605] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[900] rmse=0.018506 lr=0.029576 +[1,0]:INFO:root:Epoch[223] Batch[1000] Loss[3.259] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[1000] rmse=0.018527 lr=0.029477 +[1,0]:INFO:root:Epoch[223] Batch[1100] Loss[2.440] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[1100] rmse=0.018537 lr=0.029379 +[1,0]:INFO:root:Epoch[223] Batch[1200] Loss[2.357] +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[1200] rmse=0.018551 lr=0.029280 +[1,0]:INFO:root:Epoch[223] Rank[0] Batch[1251] Time cost=398.98 Train-metric=0.018554 +[1,0]:INFO:root:Epoch[223] Speed: 3210.73 samples/sec +[1,0]:INFO:root:Epoch[224] Batch[100] Loss[3.846] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[100] rmse=0.018342 lr=0.029131 +[1,0]:INFO:root:Epoch[224] Batch[200] Loss[2.554] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[200] rmse=0.018415 lr=0.029033 +[1,0]:INFO:root:Epoch[224] Batch[300] Loss[2.065] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[300] rmse=0.018441 lr=0.028934 +[1,0]:INFO:root:Epoch[224] Batch[400] Loss[2.477] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[400] rmse=0.018469 lr=0.028836 +[1,0]:INFO:root:Epoch[224] Batch[500] Loss[2.317] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[500] rmse=0.018459 lr=0.028739 +[1,0]:INFO:root:Epoch[224] Batch[600] Loss[4.635] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[600] rmse=0.018453 lr=0.028641 +[1,0]:INFO:root:Epoch[224] Batch[700] Loss[2.487] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[700] rmse=0.018439 lr=0.028543 +[1,0]:INFO:root:Epoch[224] Batch[800] Loss[3.706] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[800] rmse=0.018455 lr=0.028446 +[1,0]:INFO:root:Epoch[224] Batch[900] Loss[3.827] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[900] rmse=0.018473 lr=0.028349 +[1,0]:INFO:root:Epoch[224] Batch[1000] Loss[2.238] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[1000] rmse=0.018482 lr=0.028251 +[1,0]:INFO:root:Epoch[224] Batch[1100] Loss[2.342] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[1100] rmse=0.018493 lr=0.028154 +[1,0]:INFO:root:Epoch[224] Batch[1200] Loss[2.278] +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[1200] rmse=0.018505 lr=0.028058 +[1,0]:INFO:root:Epoch[224] Rank[0] Batch[1251] Time cost=399.92 Train-metric=0.018514 +[1,0]:INFO:root:Epoch[224] Speed: 3203.19 samples/sec +[1,0]:INFO:root:Epoch[224] Rank[0] Validation-accuracy=0.727260 Validation-top_k_accuracy_5=0.910560 +[1,0]:INFO:root:Epoch[225] Batch[100] Loss[2.467] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[100] rmse=0.018521 lr=0.027912 +[1,0]:INFO:root:Epoch[225] Batch[200] Loss[4.256] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[200] rmse=0.018534 lr=0.027815 +[1,0]:INFO:root:Epoch[225] Batch[300] Loss[2.552] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[300] rmse=0.018523 lr=0.027719 +[1,0]:INFO:root:Epoch[225] Batch[400] Loss[3.071] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[400] rmse=0.018502 lr=0.027623 +[1,0]:INFO:root:Epoch[225] Batch[500] Loss[2.331] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[500] rmse=0.018504 lr=0.027527 +[1,0]:INFO:root:Epoch[225] Batch[600] Loss[2.661] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[600] rmse=0.018538 lr=0.027431 +[1,0]:INFO:root:Epoch[225] Batch[700] Loss[2.923] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[700] rmse=0.018547 lr=0.027336 +[1,0]:INFO:root:Epoch[225] Batch[800] Loss[3.497] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[800] rmse=0.018548 lr=0.027240 +[1,0]:INFO:root:Epoch[225] Batch[900] Loss[2.330] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[900] rmse=0.018536 lr=0.027145 +[1,0]:INFO:root:Epoch[225] Batch[1000] Loss[2.331] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[1000] rmse=0.018537 lr=0.027050 +[1,0]:INFO:root:Epoch[225] Batch[1100] Loss[4.681] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[1100] rmse=0.018532 lr=0.026955 +[1,0]:INFO:root:Epoch[225] Batch[1200] Loss[2.183] +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[1200] rmse=0.018540 lr=0.026860 +[1,0]:INFO:root:Epoch[225] Rank[0] Batch[1251] Time cost=403.08 Train-metric=0.018539 +[1,0]:INFO:root:Epoch[225] Speed: 3178.06 samples/sec +[1,0]:INFO:root:Epoch[226] Batch[100] Loss[4.573] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[100] rmse=0.018389 lr=0.026717 +[1,0]:INFO:root:Epoch[226] Batch[200] Loss[2.419] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[200] rmse=0.018420 lr=0.026622 +[1,0]:INFO:root:Epoch[226] Batch[300] Loss[2.253] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[300] rmse=0.018406 lr=0.026528 +[1,0]:INFO:root:Epoch[226] Batch[400] Loss[2.580] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[400] rmse=0.018403 lr=0.026434 +[1,0]:INFO:root:Epoch[226] Batch[500] Loss[3.933] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[500] rmse=0.018439 lr=0.026340 +[1,0]:INFO:root:Epoch[226] Batch[600] Loss[4.948] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[600] rmse=0.018454 lr=0.026246 +[1,0]:INFO:root:Epoch[226] Batch[700] Loss[2.245] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[700] rmse=0.018464 lr=0.026152 +[1,0]:INFO:root:Epoch[226] Batch[800] Loss[4.338] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[800] rmse=0.018477 lr=0.026059 +[1,0]:INFO:root:Epoch[226] Batch[900] Loss[2.425] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[900] rmse=0.018471 lr=0.025965 +[1,0]:INFO:root:Epoch[226] Batch[1000] Loss[2.371] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[1000] rmse=0.018464 lr=0.025872 +[1,0]:INFO:root:Epoch[226] Batch[1100] Loss[4.439] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[1100] rmse=0.018472 lr=0.025779 +[1,0]:INFO:root:Epoch[226] Batch[1200] Loss[2.609] +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[1200] rmse=0.018468 lr=0.025686 +[1,0]:INFO:root:Epoch[226] Rank[0] Batch[1251] Time cost=402.85 Train-metric=0.018475 +[1,0]:INFO:root:Epoch[226] Speed: 3179.88 samples/sec +[1,0]:INFO:root:Epoch[227] Batch[100] Loss[2.304] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[100] rmse=0.018276 lr=0.025546 +[1,0]:INFO:root:Epoch[227] Batch[200] Loss[2.310] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[200] rmse=0.018415 lr=0.025453 +[1,0]:INFO:root:Epoch[227] Batch[300] Loss[2.264] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[300] rmse=0.018370 lr=0.025361 +[1,0]:INFO:root:Epoch[227] Batch[400] Loss[2.144] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[400] rmse=0.018370 lr=0.025269 +[1,0]:INFO:root:Epoch[227] Batch[500] Loss[2.189] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[500] rmse=0.018370 lr=0.025177 +[1,0]:INFO:root:Epoch[227] Batch[600] Loss[4.051] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[600] rmse=0.018421 lr=0.025085 +[1,0]:INFO:root:Epoch[227] Batch[700] Loss[4.592] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[700] rmse=0.018436 lr=0.024993 +[1,0]:INFO:root:Epoch[227] Batch[800] Loss[2.027] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[800] rmse=0.018445 lr=0.024901 +[1,0]:INFO:root:Epoch[227] Batch[900] Loss[2.229] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[900] rmse=0.018439 lr=0.024810 +[1,0]:INFO:root:Epoch[227] Batch[1000] Loss[4.676] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[1000] rmse=0.018443 lr=0.024719 +[1,0]:INFO:root:Epoch[227] Batch[1100] Loss[2.543] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[1100] rmse=0.018456 lr=0.024628 +[1,0]:INFO:root:Epoch[227] Batch[1200] Loss[2.212] +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[1200] rmse=0.018470 lr=0.024537 +[1,0]:INFO:root:Epoch[227] Rank[0] Batch[1251] Time cost=404.24 Train-metric=0.018459 +[1,0]:INFO:root:Epoch[227] Speed: 3169.00 samples/sec +[1,0]:INFO:root:Epoch[228] Batch[100] Loss[2.242] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[100] rmse=0.018395 lr=0.024400 +[1,0]:INFO:root:Epoch[228] Batch[200] Loss[2.337] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[200] rmse=0.018345 lr=0.024309 +[1,0]:INFO:root:Epoch[228] Batch[300] Loss[2.328] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[300] rmse=0.018365 lr=0.024219 +[1,0]:INFO:root:Epoch[228] Batch[400] Loss[2.125] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[400] rmse=0.018391 lr=0.024128 +[1,0]:INFO:root:Epoch[228] Batch[500] Loss[2.572] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[500] rmse=0.018401 lr=0.024038 +[1,0]:INFO:root:Epoch[228] Batch[600] Loss[3.847] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[600] rmse=0.018392 lr=0.023948 +[1,0]:INFO:root:Epoch[228] Batch[700] Loss[2.307] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[700] rmse=0.018397 lr=0.023859 +[1,0]:INFO:root:Epoch[228] Batch[800] Loss[2.427] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[800] rmse=0.018411 lr=0.023769 +[1,0]:INFO:root:Epoch[228] Batch[900] Loss[2.795] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[900] rmse=0.018414 lr=0.023680 +[1,0]:INFO:root:Epoch[228] Batch[1000] Loss[4.395] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[1000] rmse=0.018433 lr=0.023590 +[1,0]:INFO:root:Epoch[228] Batch[1100] Loss[2.368] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[1100] rmse=0.018426 lr=0.023501 +[1,0]:INFO:root:Epoch[228] Batch[1200] Loss[2.377] +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[1200] rmse=0.018434 lr=0.023412 +[1,0]:INFO:root:Epoch[228] Rank[0] Batch[1251] Time cost=401.70 Train-metric=0.018435 +[1,0]:INFO:root:Epoch[228] Speed: 3189.03 samples/sec +[1,0]:INFO:root:Epoch[229] Batch[100] Loss[4.314] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[100] rmse=0.018317 lr=0.023278 +[1,0]:INFO:root:Epoch[229] Batch[200] Loss[4.020] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[200] rmse=0.018333 lr=0.023189 +[1,0]:INFO:root:Epoch[229] Batch[300] Loss[2.749] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[300] rmse=0.018316 lr=0.023101 +[1,0]:INFO:root:Epoch[229] Batch[400] Loss[2.383] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[400] rmse=0.018332 lr=0.023013 +[1,0]:INFO:root:Epoch[229] Batch[500] Loss[2.034] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[500] rmse=0.018324 lr=0.022925 +[1,0]:INFO:root:Epoch[229] Batch[600] Loss[2.349] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[600] rmse=0.018306 lr=0.022837 +[1,0]:INFO:root:Epoch[229] Batch[700] Loss[2.553] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[700] rmse=0.018327 lr=0.022749 +[1,0]:INFO:root:Epoch[229] Batch[800] Loss[3.021] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[800] rmse=0.018345 lr=0.022661 +[1,0]:INFO:root:Epoch[229] Batch[900] Loss[4.713] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[900] rmse=0.018338 lr=0.022574 +[1,0]:INFO:root:Epoch[229] Batch[1000] Loss[2.282] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[1000] rmse=0.018348 lr=0.022486 +[1,0]:INFO:root:Epoch[229] Batch[1100] Loss[3.603] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[1100] rmse=0.018363 lr=0.022399 +[1,0]:INFO:root:Epoch[229] Batch[1200] Loss[2.377] +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[1200] rmse=0.018362 lr=0.022312 +[1,0]:INFO:root:Epoch[229] Rank[0] Batch[1251] Time cost=399.79 Train-metric=0.018359 +[1,0]:INFO:root:Epoch[229] Speed: 3204.24 samples/sec +[1,0]:INFO:root:Epoch[229] Rank[0] Validation-accuracy=0.732360 Validation-top_k_accuracy_5=0.910980 +[1,0]:INFO:root:Epoch[230] Batch[100] Loss[2.357] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[100] rmse=0.018225 lr=0.022181 +[1,0]:INFO:root:Epoch[230] Batch[200] Loss[2.338] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[200] rmse=0.018280 lr=0.022095 +[1,0]:INFO:root:Epoch[230] Batch[300] Loss[2.516] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[300] rmse=0.018285 lr=0.022008 +[1,0]:INFO:root:Epoch[230] Batch[400] Loss[2.174] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[400] rmse=0.018304 lr=0.021922 +[1,0]:INFO:root:Epoch[230] Batch[500] Loss[2.237] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[500] rmse=0.018330 lr=0.021836 +[1,0]:INFO:root:Epoch[230] Batch[600] Loss[2.116] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[600] rmse=0.018307 lr=0.021750 +[1,0]:INFO:root:Epoch[230] Batch[700] Loss[3.200] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[700] rmse=0.018309 lr=0.021664 +[1,0]:INFO:root:Epoch[230] Batch[800] Loss[4.145] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[800] rmse=0.018298 lr=0.021578 +[1,0]:INFO:root:Epoch[230] Batch[900] Loss[4.928] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[900] rmse=0.018304 lr=0.021493 +[1,0]:INFO:root:Epoch[230] Batch[1000] Loss[2.424] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[1000] rmse=0.018309 lr=0.021407 +[1,0]:INFO:root:Epoch[230] Batch[1100] Loss[2.494] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[1100] rmse=0.018323 lr=0.021322 +[1,0]:INFO:root:Epoch[230] Batch[1200] Loss[2.390] +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[1200] rmse=0.018337 lr=0.021237 +[1,0]:INFO:root:Epoch[230] Rank[0] Batch[1251] Time cost=399.09 Train-metric=0.018334 +[1,0]:INFO:root:Epoch[230] Speed: 3209.90 samples/sec +[1,0]:INFO:root:Epoch[231] Batch[100] Loss[2.309] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[100] rmse=0.018237 lr=0.021109 +[1,0]:INFO:root:Epoch[231] Batch[200] Loss[2.860] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[200] rmse=0.018275 lr=0.021025 +[1,0]:INFO:root:Epoch[231] Batch[300] Loss[2.761] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[300] rmse=0.018242 lr=0.020940 +[1,0]:INFO:root:Epoch[231] Batch[400] Loss[2.371] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[400] rmse=0.018253 lr=0.020856 +[1,0]:INFO:root:Epoch[231] Batch[500] Loss[3.828] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[500] rmse=0.018246 lr=0.020772 +[1,0]:INFO:root:Epoch[231] Batch[600] Loss[2.403] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[600] rmse=0.018259 lr=0.020688 +[1,0]:INFO:root:Epoch[231] Batch[700] Loss[4.090] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[700] rmse=0.018283 lr=0.020604 +[1,0]:INFO:root:Epoch[231] Batch[800] Loss[4.892] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[800] rmse=0.018285 lr=0.020520 +[1,0]:INFO:root:Epoch[231] Batch[900] Loss[4.623] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[900] rmse=0.018289 lr=0.020437 +[1,0]:INFO:root:Epoch[231] Batch[1000] Loss[2.218] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[1000] rmse=0.018299 lr=0.020354 +[1,0]:INFO:root:Epoch[231] Batch[1100] Loss[2.169] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[1100] rmse=0.018295 lr=0.020270 +[1,0]:INFO:root:Epoch[231] Batch[1200] Loss[2.286] +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[1200] rmse=0.018296 lr=0.020187 +[1,0]:INFO:root:Epoch[231] Rank[0] Batch[1251] Time cost=399.34 Train-metric=0.018305 +[1,0]:INFO:root:Epoch[231] Speed: 3207.84 samples/sec +[1,0]:INFO:root:Epoch[232] Batch[100] Loss[2.446] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[100] rmse=0.018154 lr=0.020062 +[1,0]:INFO:root:Epoch[232] Batch[200] Loss[2.968] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[200] rmse=0.018203 lr=0.019980 +[1,0]:INFO:root:Epoch[232] Batch[300] Loss[2.861] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[300] rmse=0.018201 lr=0.019897 +[1,0]:INFO:root:Epoch[232] Batch[400] Loss[2.220] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[400] rmse=0.018222 lr=0.019815 +[1,0]:INFO:root:Epoch[232] Batch[500] Loss[3.471] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[500] rmse=0.018249 lr=0.019733 +[1,0]:INFO:root:Epoch[232] Batch[600] Loss[2.147] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[600] rmse=0.018263 lr=0.019651 +[1,0]:INFO:root:Epoch[232] Batch[700] Loss[3.073] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[700] rmse=0.018269 lr=0.019569 +[1,0]:INFO:root:Epoch[232] Batch[800] Loss[2.364] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[800] rmse=0.018280 lr=0.019488 +[1,0]:INFO:root:Epoch[232] Batch[900] Loss[2.583] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[900] rmse=0.018273 lr=0.019406 +[1,0]:INFO:root:Epoch[232] Batch[1000] Loss[4.621] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[1000] rmse=0.018275 lr=0.019325 +[1,0]:INFO:root:Epoch[232] Batch[1100] Loss[2.644] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[1100] rmse=0.018277 lr=0.019244 +[1,0]:INFO:root:Epoch[232] Batch[1200] Loss[2.341] +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[1200] rmse=0.018271 lr=0.019163 +[1,0]:INFO:root:Epoch[232] Rank[0] Batch[1251] Time cost=399.78 Train-metric=0.018269 +[1,0]:INFO:root:Epoch[232] Speed: 3204.33 samples/sec +[1,0]:INFO:root:Epoch[233] Batch[100] Loss[2.814] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[100] rmse=0.018117 lr=0.019041 +[1,0]:INFO:root:Epoch[233] Batch[200] Loss[2.364] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[200] rmse=0.018136 lr=0.018960 +[1,0]:INFO:root:Epoch[233] Batch[300] Loss[2.449] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[300] rmse=0.018157 lr=0.018880 +[1,0]:INFO:root:Epoch[233] Batch[400] Loss[2.231] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[400] rmse=0.018189 lr=0.018800 +[1,0]:INFO:root:Epoch[233] Batch[500] Loss[2.304] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[500] rmse=0.018205 lr=0.018720 +[1,0]:INFO:root:Epoch[233] Batch[600] Loss[3.311] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[600] rmse=0.018195 lr=0.018640 +[1,0]:INFO:root:Epoch[233] Batch[700] Loss[2.046] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[700] rmse=0.018184 lr=0.018560 +[1,0]:INFO:root:Epoch[233] Batch[800] Loss[2.617] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[800] rmse=0.018187 lr=0.018480 +[1,0]:INFO:root:Epoch[233] Batch[900] Loss[2.027] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[900] rmse=0.018189 lr=0.018401 +[1,0]:INFO:root:Epoch[233] Batch[1000] Loss[2.361] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[1000] rmse=0.018185 lr=0.018322 +[1,0]:INFO:root:Epoch[233] Batch[1100] Loss[2.139] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[1100] rmse=0.018200 lr=0.018243 +[1,0]:INFO:root:Epoch[233] Batch[1200] Loss[2.361] +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[1200] rmse=0.018204 lr=0.018164 +[1,0]:INFO:root:Epoch[233] Rank[0] Batch[1251] Time cost=399.16 Train-metric=0.018199 +[1,0]:INFO:root:Epoch[233] Speed: 3209.29 samples/sec +[1,0]:INFO:root:Epoch[234] Batch[100] Loss[2.418] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[100] rmse=0.018117 lr=0.018045 +[1,0]:INFO:root:Epoch[234] Batch[200] Loss[3.945] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[200] rmse=0.018101 lr=0.017966 +[1,0]:INFO:root:Epoch[234] Batch[300] Loss[4.423] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[300] rmse=0.018143 lr=0.017888 +[1,0]:INFO:root:Epoch[234] Batch[400] Loss[3.033] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[400] rmse=0.018147 lr=0.017810 +[1,0]:INFO:root:Epoch[234] Batch[500] Loss[2.512] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[500] rmse=0.018134 lr=0.017732 +[1,0]:INFO:root:Epoch[234] Batch[600] Loss[2.789] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[600] rmse=0.018154 lr=0.017654 +[1,0]:INFO:root:Epoch[234] Batch[700] Loss[2.322] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[700] rmse=0.018172 lr=0.017576 +[1,0]:INFO:root:Epoch[234] Batch[800] Loss[2.351] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[800] rmse=0.018176 lr=0.017498 +[1,0]:INFO:root:Epoch[234] Batch[900] Loss[4.293] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[900] rmse=0.018197 lr=0.017421 +[1,0]:INFO:root:Epoch[234] Batch[1000] Loss[2.262] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[1000] rmse=0.018206 lr=0.017344 +[1,0]:INFO:root:Epoch[234] Batch[1100] Loss[2.305] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[1100] rmse=0.018201 lr=0.017267 +[1,0]:INFO:root:Epoch[234] Batch[1200] Loss[2.811] +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[1200] rmse=0.018208 lr=0.017190 +[1,0]:INFO:root:Epoch[234] Rank[0] Batch[1251] Time cost=399.51 Train-metric=0.018198 +[1,0]:INFO:root:Epoch[234] Speed: 3206.48 samples/sec +[1,0]:INFO:root:Epoch[234] Rank[0] Validation-accuracy=0.734900 Validation-top_k_accuracy_5=0.915180 +[1,0]:INFO:root:Epoch[235] Batch[100] Loss[2.991] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[100] rmse=0.018036 lr=0.017074 +[1,0]:INFO:root:Epoch[235] Batch[200] Loss[2.623] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[200] rmse=0.018189 lr=0.016998 +[1,0]:INFO:root:Epoch[235] Batch[300] Loss[2.968] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[300] rmse=0.018169 lr=0.016921 +[1,0]:INFO:root:Epoch[235] Batch[400] Loss[2.585] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[400] rmse=0.018138 lr=0.016845 +[1,0]:INFO:root:Epoch[235] Batch[500] Loss[2.554] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[500] rmse=0.018133 lr=0.016769 +[1,0]:INFO:root:Epoch[235] Batch[600] Loss[2.602] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[600] rmse=0.018111 lr=0.016693 +[1,0]:INFO:root:Epoch[235] Batch[700] Loss[2.927] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[700] rmse=0.018119 lr=0.016618 +[1,0]:INFO:root:Epoch[235] Batch[800] Loss[2.169] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[800] rmse=0.018133 lr=0.016542 +[1,0]:INFO:root:Epoch[235] Batch[900] Loss[2.480] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[900] rmse=0.018129 lr=0.016467 +[1,0]:INFO:root:Epoch[235] Batch[1000] Loss[4.923] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[1000] rmse=0.018134 lr=0.016392 +[1,0]:INFO:root:Epoch[235] Batch[1100] Loss[2.419] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[1100] rmse=0.018126 lr=0.016317 +[1,0]:INFO:root:Epoch[235] Batch[1200] Loss[4.569] +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[1200] rmse=0.018140 lr=0.016242 +[1,0]:INFO:root:Epoch[235] Rank[0] Batch[1251] Time cost=398.90 Train-metric=0.018144 +[1,0]:INFO:root:Epoch[235] Speed: 3211.42 samples/sec +[1,0]:INFO:root:Epoch[236] Batch[100] Loss[2.374] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[100] rmse=0.018061 lr=0.016129 +[1,0]:INFO:root:Epoch[236] Batch[200] Loss[2.193] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[200] rmse=0.018095 lr=0.016055 +[1,0]:INFO:root:Epoch[236] Batch[300] Loss[4.856] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[300] rmse=0.018139 lr=0.015980 +[1,0]:INFO:root:Epoch[236] Batch[400] Loss[2.194] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[400] rmse=0.018119 lr=0.015906 +[1,0]:INFO:root:Epoch[236] Batch[500] Loss[3.484] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[500] rmse=0.018105 lr=0.015832 +[1,0]:INFO:root:Epoch[236] Batch[600] Loss[2.265] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[600] rmse=0.018107 lr=0.015759 +[1,0]:INFO:root:Epoch[236] Batch[700] Loss[3.747] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[700] rmse=0.018105 lr=0.015685 +[1,0]:INFO:root:Epoch[236] Batch[800] Loss[2.126] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[800] rmse=0.018108 lr=0.015612 +[1,0]:INFO:root:Epoch[236] Batch[900] Loss[3.078] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[900] rmse=0.018113 lr=0.015538 +[1,0]:INFO:root:Epoch[236] Batch[1000] Loss[2.314] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[1000] rmse=0.018120 lr=0.015465 +[1,0]:INFO:root:Epoch[236] Batch[1100] Loss[3.123] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[1100] rmse=0.018124 lr=0.015392 +[1,0]:INFO:root:Epoch[236] Batch[1200] Loss[4.294] +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[1200] rmse=0.018121 lr=0.015320 +[1,0]:INFO:root:Epoch[236] Rank[0] Batch[1251] Time cost=399.14 Train-metric=0.018127 +[1,0]:INFO:root:Epoch[236] Speed: 3209.44 samples/sec +[1,0]:INFO:root:Epoch[237] Batch[100] Loss[2.633] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[100] rmse=0.017955 lr=0.015210 +[1,0]:INFO:root:Epoch[237] Batch[200] Loss[2.295] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[200] rmse=0.018030 lr=0.015138 +[1,0]:INFO:root:Epoch[237] Batch[300] Loss[3.551] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[300] rmse=0.018050 lr=0.015065 +[1,0]:INFO:root:Epoch[237] Batch[400] Loss[2.163] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[400] rmse=0.018036 lr=0.014993 +[1,0]:INFO:root:Epoch[237] Batch[500] Loss[2.257] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[500] rmse=0.018077 lr=0.014922 +[1,0]:INFO:root:Epoch[237] Batch[600] Loss[2.241] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[600] rmse=0.018081 lr=0.014850 +[1,0]:INFO:root:Epoch[237] Batch[700] Loss[3.879] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[700] rmse=0.018073 lr=0.014778 +[1,0]:INFO:root:Epoch[237] Batch[800] Loss[2.259] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[800] rmse=0.018081 lr=0.014707 +[1,0]:INFO:root:Epoch[237] Batch[900] Loss[4.666] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[900] rmse=0.018077 lr=0.014636 +[1,0]:INFO:root:Epoch[237] Batch[1000] Loss[2.930] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[1000] rmse=0.018084 lr=0.014565 +[1,0]:INFO:root:Epoch[237] Batch[1100] Loss[4.466] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[1100] rmse=0.018080 lr=0.014494 +[1,0]:INFO:root:Epoch[237] Batch[1200] Loss[2.644] +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[1200] rmse=0.018075 lr=0.014423 +[1,0]:INFO:root:Epoch[237] Rank[0] Batch[1251] Time cost=400.20 Train-metric=0.018082 +[1,0]:INFO:root:Epoch[237] Speed: 3200.99 samples/sec +[1,0]:INFO:root:Epoch[238] Batch[100] Loss[2.153] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[100] rmse=0.017962 lr=0.014317 +[1,0]:INFO:root:Epoch[238] Batch[200] Loss[2.582] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[200] rmse=0.017922 lr=0.014246 +[1,0]:INFO:root:Epoch[238] Batch[300] Loss[3.679] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[300] rmse=0.017980 lr=0.014176 +[1,0]:INFO:root:Epoch[238] Batch[400] Loss[1.962] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[400] rmse=0.017984 lr=0.014106 +[1,0]:INFO:root:Epoch[238] Batch[500] Loss[2.659] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[500] rmse=0.018000 lr=0.014037 +[1,0]:INFO:root:Epoch[238] Batch[600] Loss[4.465] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[600] rmse=0.018002 lr=0.013967 +[1,0]:INFO:root:Epoch[238] Batch[700] Loss[2.143] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[700] rmse=0.018031 lr=0.013898 +[1,0]:INFO:root:Epoch[238] Batch[800] Loss[3.870] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[800] rmse=0.018039 lr=0.013828 +[1,0]:INFO:root:Epoch[238] Batch[900] Loss[2.426] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[900] rmse=0.018035 lr=0.013759 +[1,0]:INFO:root:Epoch[238] Batch[1000] Loss[2.663] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[1000] rmse=0.018038 lr=0.013690 +[1,0]:INFO:root:Epoch[238] Batch[1100] Loss[2.316] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[1100] rmse=0.018023 lr=0.013621 +[1,0]:INFO:root:Epoch[238] Batch[1200] Loss[2.081] +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[1200] rmse=0.018033 lr=0.013553 +[1,0]:INFO:root:Epoch[238] Rank[0] Batch[1251] Time cost=399.42 Train-metric=0.018037 +[1,0]:INFO:root:Epoch[238] Speed: 3207.20 samples/sec +[1,0]:INFO:root:Epoch[239] Batch[100] Loss[2.695] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[100] rmse=0.017806 lr=0.013450 +[1,0]:INFO:root:Epoch[239] Batch[200] Loss[3.960] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[200] rmse=0.017864 lr=0.013381 +[1,0]:INFO:root:Epoch[239] Batch[300] Loss[2.395] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[300] rmse=0.017905 lr=0.013313 +[1,0]:INFO:root:Epoch[239] Batch[400] Loss[3.643] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[400] rmse=0.017921 lr=0.013245 +[1,0]:INFO:root:Epoch[239] Batch[500] Loss[2.201] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[500] rmse=0.017956 lr=0.013178 +[1,0]:INFO:root:Epoch[239] Batch[600] Loss[4.658] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[600] rmse=0.017982 lr=0.013110 +[1,0]:INFO:root:Epoch[239] Batch[700] Loss[2.289] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[700] rmse=0.017991 lr=0.013043 +[1,0]:INFO:root:Epoch[239] Batch[800] Loss[2.548] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[800] rmse=0.017986 lr=0.012976 +[1,0]:INFO:root:Epoch[239] Batch[900] Loss[3.650] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[900] rmse=0.017989 lr=0.012909 +[1,0]:INFO:root:Epoch[239] Batch[1000] Loss[2.307] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[1000] rmse=0.017974 lr=0.012842 +[1,0]:INFO:root:Epoch[239] Batch[1100] Loss[4.391] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[1100] rmse=0.017976 lr=0.012775 +[1,0]:INFO:root:Epoch[239] Batch[1200] Loss[2.130] +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[1200] rmse=0.017992 lr=0.012709 +[1,0]:INFO:root:Epoch[239] Rank[0] Batch[1251] Time cost=398.72 Train-metric=0.017997 +[1,0]:INFO:root:Epoch[239] Speed: 3212.81 samples/sec +[1,0]:INFO:root:Epoch[239] Rank[0] Validation-accuracy=0.741840 Validation-top_k_accuracy_5=0.918000 +[1,0]:INFO:root:Epoch[240] Batch[100] Loss[2.392] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[100] rmse=0.017917 lr=0.012609 +[1,0]:INFO:root:Epoch[240] Batch[200] Loss[2.570] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[200] rmse=0.017938 lr=0.012542 +[1,0]:INFO:root:Epoch[240] Batch[300] Loss[2.310] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[300] rmse=0.017920 lr=0.012477 +[1,0]:INFO:root:Epoch[240] Batch[400] Loss[2.254] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[400] rmse=0.017909 lr=0.012411 +[1,0]:INFO:root:Epoch[240] Batch[500] Loss[2.271] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[500] rmse=0.017942 lr=0.012345 +[1,0]:INFO:root:Epoch[240] Batch[600] Loss[2.336] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[600] rmse=0.017938 lr=0.012280 +[1,0]:INFO:root:Epoch[240] Batch[700] Loss[2.321] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[700] rmse=0.017962 lr=0.012215 +[1,0]:INFO:root:Epoch[240] Batch[800] Loss[2.175] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[800] rmse=0.017963 lr=0.012149 +[1,0]:INFO:root:Epoch[240] Batch[900] Loss[2.155] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[900] rmse=0.017975 lr=0.012085 +[1,0]:INFO:root:Epoch[240] Batch[1000] Loss[3.330] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[1000] rmse=0.017988 lr=0.012020 +[1,0]:INFO:root:Epoch[240] Batch[1100] Loss[4.544] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[1100] rmse=0.017981 lr=0.011955 +[1,0]:INFO:root:Epoch[240] Batch[1200] Loss[2.203] +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[1200] rmse=0.017977 lr=0.011891 +[1,0]:INFO:root:Epoch[240] Rank[0] Batch[1251] Time cost=397.51 Train-metric=0.017970 +[1,0]:INFO:root:Epoch[240] Speed: 3222.64 samples/sec +[1,0]:INFO:root:Epoch[241] Batch[100] Loss[4.880] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[100] rmse=0.017921 lr=0.011794 +[1,0]:INFO:root:Epoch[241] Batch[200] Loss[1.931] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[200] rmse=0.017940 lr=0.011730 +[1,0]:INFO:root:Epoch[241] Batch[300] Loss[2.959] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[300] rmse=0.017949 lr=0.011666 +[1,0]:INFO:root:Epoch[241] Batch[400] Loss[4.788] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[400] rmse=0.017967 lr=0.011602 +[1,0]:INFO:root:Epoch[241] Batch[500] Loss[2.046] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[500] rmse=0.017943 lr=0.011539 +[1,0]:INFO:root:Epoch[241] Batch[600] Loss[2.458] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[600] rmse=0.017948 lr=0.011476 +[1,0]:INFO:root:Epoch[241] Batch[700] Loss[2.283] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[700] rmse=0.017929 lr=0.011412 +[1,0]:INFO:root:Epoch[241] Batch[800] Loss[2.146] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[800] rmse=0.017937 lr=0.011349 +[1,0]:INFO:root:Epoch[241] Batch[900] Loss[2.445] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[900] rmse=0.017927 lr=0.011287 +[1,0]:INFO:root:Epoch[241] Batch[1000] Loss[2.792] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[1000] rmse=0.017926 lr=0.011224 +[1,0]:INFO:root:Epoch[241] Batch[1100] Loss[3.178] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[1100] rmse=0.017929 lr=0.011162 +[1,0]:INFO:root:Epoch[241] Batch[1200] Loss[2.021] +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[1200] rmse=0.017925 lr=0.011099 +[1,0]:INFO:root:Epoch[241] Rank[0] Batch[1251] Time cost=399.30 Train-metric=0.017927 +[1,0]:INFO:root:Epoch[241] Speed: 3208.19 samples/sec +[1,0]:INFO:root:Epoch[242] Batch[100] Loss[2.023] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[100] rmse=0.017846 lr=0.011006 +[1,0]:INFO:root:Epoch[242] Batch[200] Loss[2.332] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[200] rmse=0.017845 lr=0.010944 +[1,0]:INFO:root:Epoch[242] Batch[300] Loss[4.760] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[300] rmse=0.017855 lr=0.010882 +[1,0]:INFO:root:Epoch[242] Batch[400] Loss[2.234] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[400] rmse=0.017844 lr=0.010820 +[1,0]:INFO:root:Epoch[242] Batch[500] Loss[4.475] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[500] rmse=0.017858 lr=0.010759 +[1,0]:INFO:root:Epoch[242] Batch[600] Loss[3.502] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[600] rmse=0.017867 lr=0.010698 +[1,0]:INFO:root:Epoch[242] Batch[700] Loss[4.662] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[700] rmse=0.017884 lr=0.010637 +[1,0]:INFO:root:Epoch[242] Batch[800] Loss[2.128] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[800] rmse=0.017883 lr=0.010576 +[1,0]:INFO:root:Epoch[242] Batch[900] Loss[2.270] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[900] rmse=0.017894 lr=0.010515 +[1,0]:INFO:root:Epoch[242] Batch[1000] Loss[2.407] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[1000] rmse=0.017910 lr=0.010455 +[1,0]:INFO:root:Epoch[242] Batch[1100] Loss[3.488] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[1100] rmse=0.017904 lr=0.010394 +[1,0]:INFO:root:Epoch[242] Batch[1200] Loss[2.221] +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[1200] rmse=0.017905 lr=0.010334 +[1,0]:INFO:root:Epoch[242] Rank[0] Batch[1251] Time cost=399.94 Train-metric=0.017897 +[1,0]:INFO:root:Epoch[242] Speed: 3203.08 samples/sec +[1,0]:INFO:root:Epoch[243] Batch[100] Loss[2.283] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[100] rmse=0.017951 lr=0.010244 +[1,0]:INFO:root:Epoch[243] Batch[200] Loss[2.223] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[200] rmse=0.017888 lr=0.010184 +[1,0]:INFO:root:Epoch[243] Batch[300] Loss[4.650] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[300] rmse=0.017893 lr=0.010124 +[1,0]:INFO:root:Epoch[243] Batch[400] Loss[2.169] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[400] rmse=0.017905 lr=0.010065 +[1,0]:INFO:root:Epoch[243] Batch[500] Loss[4.900] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[500] rmse=0.017869 lr=0.010006 +[1,0]:INFO:root:Epoch[243] Batch[600] Loss[3.333] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[600] rmse=0.017852 lr=0.009947 +[1,0]:INFO:root:Epoch[243] Batch[700] Loss[3.512] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[700] rmse=0.017829 lr=0.009888 +[1,0]:INFO:root:Epoch[243] Batch[800] Loss[2.269] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[800] rmse=0.017821 lr=0.009829 +[1,0]:INFO:root:Epoch[243] Batch[900] Loss[2.306] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[900] rmse=0.017837 lr=0.009771 +[1,0]:INFO:root:Epoch[243] Batch[1000] Loss[4.639] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[1000] rmse=0.017844 lr=0.009712 +[1,0]:INFO:root:Epoch[243] Batch[1100] Loss[2.575] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[1100] rmse=0.017833 lr=0.009654 +[1,0]:INFO:root:Epoch[243] Batch[1200] Loss[2.644] +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[1200] rmse=0.017834 lr=0.009596 +[1,0]:INFO:root:Epoch[243] Rank[0] Batch[1251] Time cost=398.95 Train-metric=0.017839 +[1,0]:INFO:root:Epoch[243] Speed: 3211.01 samples/sec +[1,0]:INFO:root:Epoch[244] Batch[100] Loss[2.411] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[100] rmse=0.017812 lr=0.009509 +[1,0]:INFO:root:Epoch[244] Batch[200] Loss[4.755] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[200] rmse=0.017844 lr=0.009451 +[1,0]:INFO:root:Epoch[244] Batch[300] Loss[2.132] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[300] rmse=0.017815 lr=0.009394 +[1,0]:INFO:root:Epoch[244] Batch[400] Loss[4.749] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[400] rmse=0.017839 lr=0.009336 +[1,0]:INFO:root:Epoch[244] Batch[500] Loss[4.510] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[500] rmse=0.017833 lr=0.009279 +[1,0]:INFO:root:Epoch[244] Batch[600] Loss[2.358] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[600] rmse=0.017859 lr=0.009222 +[1,0]:INFO:root:Epoch[244] Batch[700] Loss[2.114] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[700] rmse=0.017841 lr=0.009165 +[1,0]:INFO:root:Epoch[244] Batch[800] Loss[4.755] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[800] rmse=0.017839 lr=0.009109 +[1,0]:INFO:root:Epoch[244] Batch[900] Loss[2.244] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[900] rmse=0.017844 lr=0.009052 +[1,0]:INFO:root:Epoch[244] Batch[1000] Loss[2.814] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[1000] rmse=0.017856 lr=0.008996 +[1,0]:INFO:root:Epoch[244] Batch[1100] Loss[2.736] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[1100] rmse=0.017847 lr=0.008940 +[1,0]:INFO:root:Epoch[244] Batch[1200] Loss[2.093] +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[1200] rmse=0.017842 lr=0.008884 +[1,0]:INFO:root:Epoch[244] Rank[0] Batch[1251] Time cost=400.08 Train-metric=0.017843 +[1,0]:INFO:root:Epoch[244] Speed: 3201.95 samples/sec +[1,0]:INFO:root:Epoch[244] Rank[0] Validation-accuracy=0.747260 Validation-top_k_accuracy_5=0.920760 +[1,0]:INFO:root:Epoch[245] Batch[100] Loss[2.231] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[100] rmse=0.017810 lr=0.008800 +[1,0]:INFO:root:Epoch[245] Batch[200] Loss[3.150] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[200] rmse=0.017774 lr=0.008745 +[1,0]:INFO:root:Epoch[245] Batch[300] Loss[4.761] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[300] rmse=0.017747 lr=0.008689 +[1,0]:INFO:root:Epoch[245] Batch[400] Loss[3.325] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[400] rmse=0.017724 lr=0.008634 +[1,0]:INFO:root:Epoch[245] Batch[500] Loss[2.245] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[500] rmse=0.017713 lr=0.008579 +[1,0]:INFO:root:Epoch[245] Batch[600] Loss[2.958] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[600] rmse=0.017735 lr=0.008525 +[1,0]:INFO:root:Epoch[245] Batch[700] Loss[2.488] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[700] rmse=0.017746 lr=0.008470 +[1,0]:INFO:root:Epoch[245] Batch[800] Loss[2.159] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[800] rmse=0.017759 lr=0.008415 +[1,0]:INFO:root:Epoch[245] Batch[900] Loss[2.176] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[900] rmse=0.017742 lr=0.008361 +[1,0]:INFO:root:Epoch[245] Batch[1000] Loss[2.207] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[1000] rmse=0.017756 lr=0.008307 +[1,0]:INFO:root:Epoch[245] Batch[1100] Loss[2.223] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[1100] rmse=0.017766 lr=0.008253 +[1,0]:INFO:root:Epoch[245] Batch[1200] Loss[4.611] +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[1200] rmse=0.017770 lr=0.008199 +[1,0]:INFO:root:Epoch[245] Rank[0] Batch[1251] Time cost=398.41 Train-metric=0.017779 +[1,0]:INFO:root:Epoch[245] Speed: 3215.33 samples/sec +[1,0]:INFO:root:Epoch[246] Batch[100] Loss[2.218] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[100] rmse=0.017727 lr=0.008119 +[1,0]:INFO:root:Epoch[246] Batch[200] Loss[3.928] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[200] rmse=0.017739 lr=0.008065 +[1,0]:INFO:root:Epoch[246] Batch[300] Loss[2.328] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[300] rmse=0.017768 lr=0.008012 +[1,0]:INFO:root:Epoch[246] Batch[400] Loss[2.820] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[400] rmse=0.017732 lr=0.007959 +[1,0]:INFO:root:Epoch[246] Batch[500] Loss[4.676] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[500] rmse=0.017719 lr=0.007906 +[1,0]:INFO:root:Epoch[246] Batch[600] Loss[4.174] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[600] rmse=0.017723 lr=0.007854 +[1,0]:INFO:root:Epoch[246] Batch[700] Loss[2.102] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[700] rmse=0.017735 lr=0.007801 +[1,0]:INFO:root:Epoch[246] Batch[800] Loss[2.479] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[800] rmse=0.017733 lr=0.007749 +[1,0]:INFO:root:Epoch[246] Batch[900] Loss[4.796] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[900] rmse=0.017713 lr=0.007697 +[1,0]:INFO:root:Epoch[246] Batch[1000] Loss[4.075] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[1000] rmse=0.017721 lr=0.007645 +[1,0]:INFO:root:Epoch[246] Batch[1100] Loss[2.530] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[1100] rmse=0.017725 lr=0.007593 +[1,0]:INFO:root:Epoch[246] Batch[1200] Loss[4.610] +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[1200] rmse=0.017736 lr=0.007542 +[1,0]:INFO:root:Epoch[246] Rank[0] Batch[1251] Time cost=398.93 Train-metric=0.017733 +[1,0]:INFO:root:Epoch[246] Speed: 3211.16 samples/sec +[1,0]:INFO:root:Epoch[247] Batch[100] Loss[2.247] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[100] rmse=0.017661 lr=0.007464 +[1,0]:INFO:root:Epoch[247] Batch[200] Loss[1.992] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[200] rmse=0.017692 lr=0.007413 +[1,0]:INFO:root:Epoch[247] Batch[300] Loss[2.150] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[300] rmse=0.017697 lr=0.007362 +[1,0]:INFO:root:Epoch[247] Batch[400] Loss[2.466] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[400] rmse=0.017682 lr=0.007311 +[1,0]:INFO:root:Epoch[247] Batch[500] Loss[4.202] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[500] rmse=0.017677 lr=0.007260 +[1,0]:INFO:root:Epoch[247] Batch[600] Loss[2.360] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[600] rmse=0.017685 lr=0.007210 +[1,0]:INFO:root:Epoch[247] Batch[700] Loss[4.814] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[700] rmse=0.017687 lr=0.007159 +[1,0]:INFO:root:Epoch[247] Batch[800] Loss[2.605] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[800] rmse=0.017693 lr=0.007109 +[1,0]:INFO:root:Epoch[247] Batch[900] Loss[4.484] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[900] rmse=0.017699 lr=0.007059 +[1,0]:INFO:root:Epoch[247] Batch[1000] Loss[2.270] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[1000] rmse=0.017705 lr=0.007010 +[1,0]:INFO:root:Epoch[247] Batch[1100] Loss[3.118] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[1100] rmse=0.017699 lr=0.006960 +[1,0]:INFO:root:Epoch[247] Batch[1200] Loss[2.338] +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[1200] rmse=0.017707 lr=0.006911 +[1,0]:INFO:root:Epoch[247] Rank[0] Batch[1251] Time cost=399.13 Train-metric=0.017713 +[1,0]:INFO:root:Epoch[247] Speed: 3209.56 samples/sec +[1,0]:INFO:root:Epoch[248] Batch[100] Loss[2.172] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[100] rmse=0.017550 lr=0.006836 +[1,0]:INFO:root:Epoch[248] Batch[200] Loss[4.440] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[200] rmse=0.017566 lr=0.006787 +[1,0]:INFO:root:Epoch[248] Batch[300] Loss[3.036] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[300] rmse=0.017614 lr=0.006738 +[1,0]:INFO:root:Epoch[248] Batch[400] Loss[3.230] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[400] rmse=0.017630 lr=0.006690 +[1,0]:INFO:root:Epoch[248] Batch[500] Loss[2.205] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[500] rmse=0.017631 lr=0.006641 +[1,0]:INFO:root:Epoch[248] Batch[600] Loss[3.973] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[600] rmse=0.017636 lr=0.006593 +[1,0]:INFO:root:Epoch[248] Batch[700] Loss[2.153] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[700] rmse=0.017637 lr=0.006545 +[1,0]:INFO:root:Epoch[248] Batch[800] Loss[4.294] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[800] rmse=0.017645 lr=0.006497 +[1,0]:INFO:root:Epoch[248] Batch[900] Loss[3.439] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[900] rmse=0.017639 lr=0.006449 +[1,0]:INFO:root:Epoch[248] Batch[1000] Loss[2.111] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[1000] rmse=0.017647 lr=0.006401 +[1,0]:INFO:root:Epoch[248] Batch[1100] Loss[2.080] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[1100] rmse=0.017664 lr=0.006354 +[1,0]:INFO:root:Epoch[248] Batch[1200] Loss[2.493] +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[1200] rmse=0.017659 lr=0.006307 +[1,0]:INFO:root:Epoch[248] Rank[0] Batch[1251] Time cost=399.93 Train-metric=0.017663 +[1,0]:INFO:root:Epoch[248] Speed: 3203.10 samples/sec +[1,0]:INFO:root:Epoch[249] Batch[100] Loss[4.404] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[100] rmse=0.017533 lr=0.006236 +[1,0]:INFO:root:Epoch[249] Batch[200] Loss[2.216] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[200] rmse=0.017626 lr=0.006189 +[1,0]:INFO:root:Epoch[249] Batch[300] Loss[2.214] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[300] rmse=0.017640 lr=0.006142 +[1,0]:INFO:root:Epoch[249] Batch[400] Loss[2.097] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[400] rmse=0.017609 lr=0.006096 +[1,0]:INFO:root:Epoch[249] Batch[500] Loss[2.685] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[500] rmse=0.017590 lr=0.006049 +[1,0]:INFO:root:Epoch[249] Batch[600] Loss[2.119] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[600] rmse=0.017597 lr=0.006003 +[1,0]:INFO:root:Epoch[249] Batch[700] Loss[2.135] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[700] rmse=0.017579 lr=0.005957 +[1,0]:INFO:root:Epoch[249] Batch[800] Loss[2.133] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[800] rmse=0.017610 lr=0.005912 +[1,0]:INFO:root:Epoch[249] Batch[900] Loss[2.271] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[900] rmse=0.017622 lr=0.005866 +[1,0]:INFO:root:Epoch[249] Batch[1000] Loss[4.339] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[1000] rmse=0.017630 lr=0.005820 +[1,0]:INFO:root:Epoch[249] Batch[1100] Loss[2.167] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[1100] rmse=0.017632 lr=0.005775 +[1,0]:INFO:root:Epoch[249] Batch[1200] Loss[2.891] +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[1200] rmse=0.017637 lr=0.005730 +[1,0]:INFO:root:Epoch[249] Rank[0] Batch[1251] Time cost=399.26 Train-metric=0.017637 +[1,0]:INFO:root:Epoch[249] Speed: 3208.50 samples/sec +[1,0]:INFO:root:Epoch[249] Rank[0] Validation-accuracy=0.751920 Validation-top_k_accuracy_5=0.923380 +[1,0]:INFO:root:Epoch[250] Batch[100] Loss[3.357] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[100] rmse=0.017636 lr=0.005662 +[1,0]:INFO:root:Epoch[250] Batch[200] Loss[4.455] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[200] rmse=0.017598 lr=0.005618 +[1,0]:INFO:root:Epoch[250] Batch[300] Loss[2.265] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[300] rmse=0.017598 lr=0.005573 +[1,0]:INFO:root:Epoch[250] Batch[400] Loss[3.628] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[400] rmse=0.017599 lr=0.005529 +[1,0]:INFO:root:Epoch[250] Batch[500] Loss[4.510] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[500] rmse=0.017622 lr=0.005485 +[1,0]:INFO:root:Epoch[250] Batch[600] Loss[1.937] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[600] rmse=0.017586 lr=0.005441 +[1,0]:INFO:root:Epoch[250] Batch[700] Loss[2.180] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[700] rmse=0.017593 lr=0.005397 +[1,0]:INFO:root:Epoch[250] Batch[800] Loss[2.234] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[800] rmse=0.017585 lr=0.005353 +[1,0]:INFO:root:Epoch[250] Batch[900] Loss[2.269] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[900] rmse=0.017566 lr=0.005310 +[1,0]:INFO:root:Epoch[250] Batch[1000] Loss[2.422] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[1000] rmse=0.017573 lr=0.005267 +[1,0]:INFO:root:Epoch[250] Batch[1100] Loss[2.445] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[1100] rmse=0.017562 lr=0.005224 +[1,0]:INFO:root:Epoch[250] Batch[1200] Loss[4.724] +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[1200] rmse=0.017559 lr=0.005181 +[1,0]:INFO:root:Epoch[250] Rank[0] Batch[1251] Time cost=400.41 Train-metric=0.017564 +[1,0]:INFO:root:Epoch[250] Speed: 3199.26 samples/sec +[1,0]:INFO:root:Epoch[251] Batch[100] Loss[2.687] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[100] rmse=0.017485 lr=0.005116 +[1,0]:INFO:root:Epoch[251] Batch[200] Loss[2.708] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[200] rmse=0.017532 lr=0.005074 +[1,0]:INFO:root:Epoch[251] Batch[300] Loss[2.173] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[300] rmse=0.017520 lr=0.005031 +[1,0]:INFO:root:Epoch[251] Batch[400] Loss[2.181] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[400] rmse=0.017557 lr=0.004989 +[1,0]:INFO:root:Epoch[251] Batch[500] Loss[4.670] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[500] rmse=0.017557 lr=0.004947 +[1,0]:INFO:root:Epoch[251] Batch[600] Loss[1.892] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[600] rmse=0.017559 lr=0.004906 +[1,0]:INFO:root:Epoch[251] Batch[700] Loss[2.078] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[700] rmse=0.017559 lr=0.004864 +[1,0]:INFO:root:Epoch[251] Batch[800] Loss[4.783] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[800] rmse=0.017536 lr=0.004823 +[1,0]:INFO:root:Epoch[251] Batch[900] Loss[2.080] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[900] rmse=0.017534 lr=0.004781 +[1,0]:INFO:root:Epoch[251] Batch[1000] Loss[3.056] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[1000] rmse=0.017531 lr=0.004740 +[1,0]:INFO:root:Epoch[251] Batch[1100] Loss[2.172] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[1100] rmse=0.017533 lr=0.004699 +[1,0]:INFO:root:Epoch[251] Batch[1200] Loss[3.791] +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[1200] rmse=0.017537 lr=0.004659 +[1,0]:INFO:root:Epoch[251] Rank[0] Batch[1251] Time cost=400.06 Train-metric=0.017547 +[1,0]:INFO:root:Epoch[251] Speed: 3202.05 samples/sec +[1,0]:INFO:root:Epoch[252] Batch[100] Loss[1.998] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[100] rmse=0.017619 lr=0.004597 +[1,0]:INFO:root:Epoch[252] Batch[200] Loss[4.450] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[200] rmse=0.017434 lr=0.004557 +[1,0]:INFO:root:Epoch[252] Batch[300] Loss[2.533] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[300] rmse=0.017484 lr=0.004517 +[1,0]:INFO:root:Epoch[252] Batch[400] Loss[2.207] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[400] rmse=0.017498 lr=0.004477 +[1,0]:INFO:root:Epoch[252] Batch[500] Loss[2.190] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[500] rmse=0.017517 lr=0.004437 +[1,0]:INFO:root:Epoch[252] Batch[600] Loss[4.264] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[600] rmse=0.017533 lr=0.004398 +[1,0]:INFO:root:Epoch[252] Batch[700] Loss[2.595] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[700] rmse=0.017531 lr=0.004358 +[1,0]:INFO:root:Epoch[252] Batch[800] Loss[2.702] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[800] rmse=0.017518 lr=0.004319 +[1,0]:INFO:root:Epoch[252] Batch[900] Loss[2.370] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[900] rmse=0.017522 lr=0.004280 +[1,0]:INFO:root:Epoch[252] Batch[1000] Loss[2.947] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[1000] rmse=0.017529 lr=0.004241 +[1,0]:INFO:root:Epoch[252] Batch[1100] Loss[2.239] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[1100] rmse=0.017533 lr=0.004203 +[1,0]:INFO:root:Epoch[252] Batch[1200] Loss[3.157] +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[1200] rmse=0.017532 lr=0.004164 +[1,0]:INFO:root:Epoch[252] Rank[0] Batch[1251] Time cost=401.33 Train-metric=0.017525 +[1,0]:INFO:root:Epoch[252] Speed: 3191.91 samples/sec +[1,0]:INFO:root:Epoch[253] Batch[100] Loss[2.616] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[100] rmse=0.017512 lr=0.004106 +[1,0]:INFO:root:Epoch[253] Batch[200] Loss[1.867] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[200] rmse=0.017495 lr=0.004068 +[1,0]:INFO:root:Epoch[253] Batch[300] Loss[2.218] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[300] rmse=0.017515 lr=0.004030 +[1,0]:INFO:root:Epoch[253] Batch[400] Loss[2.543] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[400] rmse=0.017521 lr=0.003992 +[1,0]:INFO:root:Epoch[253] Batch[500] Loss[2.130] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[500] rmse=0.017537 lr=0.003955 +[1,0]:INFO:root:Epoch[253] Batch[600] Loss[2.085] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[600] rmse=0.017512 lr=0.003917 +[1,0]:INFO:root:Epoch[253] Batch[700] Loss[4.058] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[700] rmse=0.017501 lr=0.003880 +[1,0]:INFO:root:Epoch[253] Batch[800] Loss[2.433] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[800] rmse=0.017507 lr=0.003843 +[1,0]:INFO:root:Epoch[253] Batch[900] Loss[2.212] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[900] rmse=0.017505 lr=0.003806 +[1,0]:INFO:root:Epoch[253] Batch[1000] Loss[1.956] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[1000] rmse=0.017506 lr=0.003770 +[1,0]:INFO:root:Epoch[253] Batch[1100] Loss[2.147] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[1100] rmse=0.017506 lr=0.003733 +[1,0]:INFO:root:Epoch[253] Batch[1200] Loss[2.018] +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[1200] rmse=0.017508 lr=0.003697 +[1,0]:INFO:root:Epoch[253] Rank[0] Batch[1251] Time cost=401.63 Train-metric=0.017511 +[1,0]:INFO:root:Epoch[253] Speed: 3189.55 samples/sec +[1,0]:INFO:root:Epoch[254] Batch[100] Loss[4.449] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[100] rmse=0.017384 lr=0.003642 +[1,0]:INFO:root:Epoch[254] Batch[200] Loss[1.913] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[200] rmse=0.017402 lr=0.003606 +[1,0]:INFO:root:Epoch[254] Batch[300] Loss[2.217] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[300] rmse=0.017387 lr=0.003571 +[1,0]:INFO:root:Epoch[254] Batch[400] Loss[2.424] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[400] rmse=0.017376 lr=0.003535 +[1,0]:INFO:root:Epoch[254] Batch[500] Loss[2.025] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[500] rmse=0.017368 lr=0.003500 +[1,0]:INFO:root:Epoch[254] Batch[600] Loss[1.999] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[600] rmse=0.017364 lr=0.003465 +[1,0]:INFO:root:Epoch[254] Batch[700] Loss[2.673] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[700] rmse=0.017388 lr=0.003430 +[1,0]:INFO:root:Epoch[254] Batch[800] Loss[2.709] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[800] rmse=0.017401 lr=0.003395 +[1,0]:INFO:root:Epoch[254] Batch[900] Loss[2.377] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[900] rmse=0.017408 lr=0.003360 +[1,0]:INFO:root:Epoch[254] Batch[1000] Loss[4.696] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[1000] rmse=0.017404 lr=0.003326 +[1,0]:INFO:root:Epoch[254] Batch[1100] Loss[2.360] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[1100] rmse=0.017409 lr=0.003291 +[1,0]:INFO:root:Epoch[254] Batch[1200] Loss[4.644] +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[1200] rmse=0.017422 lr=0.003257 +[1,0]:INFO:root:Epoch[254] Rank[0] Batch[1251] Time cost=400.29 Train-metric=0.017430 +[1,0]:INFO:root:Epoch[254] Speed: 3200.23 samples/sec +[1,0]:INFO:root:Epoch[254] Rank[0] Validation-accuracy=0.754500 Validation-top_k_accuracy_5=0.925100 +[1,0]:INFO:root:Epoch[255] Batch[100] Loss[2.094] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[100] rmse=0.017456 lr=0.003206 +[1,0]:INFO:root:Epoch[255] Batch[200] Loss[2.480] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[200] rmse=0.017391 lr=0.003172 +[1,0]:INFO:root:Epoch[255] Batch[300] Loss[4.364] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[300] rmse=0.017423 lr=0.003139 +[1,0]:INFO:root:Epoch[255] Batch[400] Loss[3.275] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[400] rmse=0.017402 lr=0.003105 +[1,0]:INFO:root:Epoch[255] Batch[500] Loss[4.836] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[500] rmse=0.017395 lr=0.003072 +[1,0]:INFO:root:Epoch[255] Batch[600] Loss[2.108] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[600] rmse=0.017406 lr=0.003039 +[1,0]:INFO:root:Epoch[255] Batch[700] Loss[4.073] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[700] rmse=0.017420 lr=0.003007 +[1,0]:INFO:root:Epoch[255] Batch[800] Loss[2.939] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[800] rmse=0.017419 lr=0.002974 +[1,0]:INFO:root:Epoch[255] Batch[900] Loss[2.079] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[900] rmse=0.017411 lr=0.002941 +[1,0]:INFO:root:Epoch[255] Batch[1000] Loss[2.255] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[1000] rmse=0.017413 lr=0.002909 +[1,0]:INFO:root:Epoch[255] Batch[1100] Loss[2.188] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[1100] rmse=0.017412 lr=0.002877 +[1,0]:INFO:root:Epoch[255] Batch[1200] Loss[4.341] +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[1200] rmse=0.017428 lr=0.002845 +[1,0]:INFO:root:Epoch[255] Rank[0] Batch[1251] Time cost=399.17 Train-metric=0.017422 +[1,0]:INFO:root:Epoch[255] Speed: 3209.23 samples/sec +[1,0]:INFO:root:Epoch[256] Batch[100] Loss[3.863] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[100] rmse=0.017428 lr=0.002797 +[1,0]:INFO:root:Epoch[256] Batch[200] Loss[2.447] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[200] rmse=0.017327 lr=0.002766 +[1,0]:INFO:root:Epoch[256] Batch[300] Loss[2.247] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[300] rmse=0.017368 lr=0.002735 +[1,0]:INFO:root:Epoch[256] Batch[400] Loss[3.791] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[400] rmse=0.017392 lr=0.002703 +[1,0]:INFO:root:Epoch[256] Batch[500] Loss[2.245] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[500] rmse=0.017377 lr=0.002673 +[1,0]:INFO:root:Epoch[256] Batch[600] Loss[2.011] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[600] rmse=0.017365 lr=0.002642 +[1,0]:INFO:root:Epoch[256] Batch[700] Loss[3.894] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[700] rmse=0.017387 lr=0.002611 +[1,0]:INFO:root:Epoch[256] Batch[800] Loss[2.020] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[800] rmse=0.017387 lr=0.002581 +[1,0]:INFO:root:Epoch[256] Batch[900] Loss[4.103] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[900] rmse=0.017381 lr=0.002550 +[1,0]:INFO:root:Epoch[256] Batch[1000] Loss[2.391] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[1000] rmse=0.017384 lr=0.002520 +[1,0]:INFO:root:Epoch[256] Batch[1100] Loss[4.746] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[1100] rmse=0.017403 lr=0.002491 +[1,0]:INFO:root:Epoch[256] Batch[1200] Loss[2.301] +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[1200] rmse=0.017408 lr=0.002461 +[1,0]:INFO:root:Epoch[256] Rank[0] Batch[1251] Time cost=399.15 Train-metric=0.017400 +[1,0]:INFO:root:Epoch[256] Speed: 3209.37 samples/sec +[1,0]:INFO:root:Epoch[257] Batch[100] Loss[4.748] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[100] rmse=0.017307 lr=0.002416 +[1,0]:INFO:root:Epoch[257] Batch[200] Loss[2.383] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[200] rmse=0.017301 lr=0.002387 +[1,0]:INFO:root:Epoch[257] Batch[300] Loss[4.270] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[300] rmse=0.017301 lr=0.002358 +[1,0]:INFO:root:Epoch[257] Batch[400] Loss[2.145] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[400] rmse=0.017305 lr=0.002329 +[1,0]:INFO:root:Epoch[257] Batch[500] Loss[4.488] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[500] rmse=0.017320 lr=0.002300 +[1,0]:INFO:root:Epoch[257] Batch[600] Loss[2.165] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[600] rmse=0.017335 lr=0.002272 +[1,0]:INFO:root:Epoch[257] Batch[700] Loss[2.474] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[700] rmse=0.017326 lr=0.002243 +[1,0]:INFO:root:Epoch[257] Batch[800] Loss[3.655] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[800] rmse=0.017341 lr=0.002215 +[1,0]:INFO:root:Epoch[257] Batch[900] Loss[1.894] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[900] rmse=0.017335 lr=0.002187 +[1,0]:INFO:root:Epoch[257] Batch[1000] Loss[2.141] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[1000] rmse=0.017346 lr=0.002159 +[1,0]:INFO:root:Epoch[257] Batch[1100] Loss[2.954] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[1100] rmse=0.017352 lr=0.002132 +[1,0]:INFO:root:Epoch[257] Batch[1200] Loss[2.627] +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[1200] rmse=0.017363 lr=0.002104 +[1,0]:INFO:root:Epoch[257] Rank[0] Batch[1251] Time cost=399.89 Train-metric=0.017368 +[1,0]:INFO:root:Epoch[257] Speed: 3203.48 samples/sec +[1,0]:INFO:root:Epoch[258] Batch[100] Loss[2.312] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[100] rmse=0.017211 lr=0.002063 +[1,0]:INFO:root:Epoch[258] Batch[200] Loss[2.771] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[200] rmse=0.017263 lr=0.002036 +[1,0]:INFO:root:Epoch[258] Batch[300] Loss[2.075] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[300] rmse=0.017278 lr=0.002009 +[1,0]:INFO:root:Epoch[258] Batch[400] Loss[4.227] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[400] rmse=0.017323 lr=0.001982 +[1,0]:INFO:root:Epoch[258] Batch[500] Loss[2.260] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[500] rmse=0.017350 lr=0.001956 +[1,0]:INFO:root:Epoch[258] Batch[600] Loss[2.383] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[600] rmse=0.017344 lr=0.001930 +[1,0]:INFO:root:Epoch[258] Batch[700] Loss[4.011] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[700] rmse=0.017344 lr=0.001903 +[1,0]:INFO:root:Epoch[258] Batch[800] Loss[3.939] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[800] rmse=0.017341 lr=0.001877 +[1,0]:INFO:root:Epoch[258] Batch[900] Loss[4.151] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[900] rmse=0.017349 lr=0.001852 +[1,0]:INFO:root:Epoch[258] Batch[1000] Loss[1.833] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[1000] rmse=0.017348 lr=0.001826 +[1,0]:INFO:root:Epoch[258] Batch[1100] Loss[1.869] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[1100] rmse=0.017333 lr=0.001801 +[1,0]:INFO:root:Epoch[258] Batch[1200] Loss[2.003] +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[1200] rmse=0.017336 lr=0.001775 +[1,0]:INFO:root:Epoch[258] Rank[0] Batch[1251] Time cost=399.96 Train-metric=0.017339 +[1,0]:INFO:root:Epoch[258] Speed: 3202.91 samples/sec +[1,0]:INFO:root:Epoch[259] Batch[100] Loss[1.965] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[100] rmse=0.017234 lr=0.001738 +[1,0]:INFO:root:Epoch[259] Batch[200] Loss[1.967] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[200] rmse=0.017191 lr=0.001713 +[1,0]:INFO:root:Epoch[259] Batch[300] Loss[2.380] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[300] rmse=0.017305 lr=0.001688 +[1,0]:INFO:root:Epoch[259] Batch[400] Loss[2.081] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[400] rmse=0.017319 lr=0.001664 +[1,0]:INFO:root:Epoch[259] Batch[500] Loss[4.133] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[500] rmse=0.017342 lr=0.001639 +[1,0]:INFO:root:Epoch[259] Batch[600] Loss[3.087] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[600] rmse=0.017341 lr=0.001615 +[1,0]:INFO:root:Epoch[259] Batch[700] Loss[2.256] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[700] rmse=0.017358 lr=0.001591 +[1,0]:INFO:root:Epoch[259] Batch[800] Loss[2.064] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[800] rmse=0.017346 lr=0.001568 +[1,0]:INFO:root:Epoch[259] Batch[900] Loss[2.154] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[900] rmse=0.017342 lr=0.001544 +[1,0]:INFO:root:Epoch[259] Batch[1000] Loss[1.936] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[1000] rmse=0.017329 lr=0.001521 +[1,0]:INFO:root:Epoch[259] Batch[1100] Loss[1.959] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[1100] rmse=0.017336 lr=0.001497 +[1,0]:INFO:root:Epoch[259] Batch[1200] Loss[2.141] +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[1200] rmse=0.017351 lr=0.001474 +[1,0]:INFO:root:Epoch[259] Rank[0] Batch[1251] Time cost=399.90 Train-metric=0.017346 +[1,0]:INFO:root:Epoch[259] Speed: 3203.33 samples/sec +[1,0]:INFO:root:Epoch[259] Rank[0] Validation-accuracy=0.757360 Validation-top_k_accuracy_5=0.926780 +[1,0]:INFO:root:Epoch[260] Batch[100] Loss[2.030] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[100] rmse=0.017196 lr=0.001440 +[1,0]:INFO:root:Epoch[260] Batch[200] Loss[2.085] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[200] rmse=0.017232 lr=0.001417 +[1,0]:INFO:root:Epoch[260] Batch[300] Loss[4.560] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[300] rmse=0.017251 lr=0.001395 +[1,0]:INFO:root:Epoch[260] Batch[400] Loss[4.102] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[400] rmse=0.017235 lr=0.001373 +[1,0]:INFO:root:Epoch[260] Batch[500] Loss[1.922] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[500] rmse=0.017240 lr=0.001351 +[1,0]:INFO:root:Epoch[260] Batch[600] Loss[2.102] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[600] rmse=0.017260 lr=0.001329 +[1,0]:INFO:root:Epoch[260] Batch[700] Loss[2.011] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[700] rmse=0.017252 lr=0.001307 +[1,0]:INFO:root:Epoch[260] Batch[800] Loss[4.566] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[800] rmse=0.017265 lr=0.001285 +[1,0]:INFO:root:Epoch[260] Batch[900] Loss[3.551] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[900] rmse=0.017264 lr=0.001264 +[1,0]:INFO:root:Epoch[260] Batch[1000] Loss[2.439] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[1000] rmse=0.017280 lr=0.001243 +[1,0]:INFO:root:Epoch[260] Batch[1100] Loss[4.135] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[1100] rmse=0.017279 lr=0.001222 +[1,0]:INFO:root:Epoch[260] Batch[1200] Loss[2.281] +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[1200] rmse=0.017276 lr=0.001201 +[1,0]:INFO:root:Epoch[260] Rank[0] Batch[1251] Time cost=397.17 Train-metric=0.017283 +[1,0]:INFO:root:Epoch[260] Speed: 3225.39 samples/sec +[1,0]:INFO:root:Epoch[261] Batch[100] Loss[2.058] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[100] rmse=0.017402 lr=0.001170 +[1,0]:INFO:root:Epoch[261] Batch[200] Loss[2.228] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[200] rmse=0.017290 lr=0.001150 +[1,0]:INFO:root:Epoch[261] Batch[300] Loss[3.992] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[300] rmse=0.017257 lr=0.001129 +[1,0]:INFO:root:Epoch[261] Batch[400] Loss[4.443] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[400] rmse=0.017244 lr=0.001109 +[1,0]:INFO:root:Epoch[261] Batch[500] Loss[2.110] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[500] rmse=0.017248 lr=0.001090 +[1,0]:INFO:root:Epoch[261] Batch[600] Loss[2.419] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[600] rmse=0.017247 lr=0.001070 +[1,0]:INFO:root:Epoch[261] Batch[700] Loss[1.778] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[700] rmse=0.017242 lr=0.001050 +[1,0]:INFO:root:Epoch[261] Batch[800] Loss[4.466] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[800] rmse=0.017253 lr=0.001031 +[1,0]:INFO:root:Epoch[261] Batch[900] Loss[2.162] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[900] rmse=0.017268 lr=0.001012 +[1,0]:INFO:root:Epoch[261] Batch[1000] Loss[1.834] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[1000] rmse=0.017274 lr=0.000993 +[1,0]:INFO:root:Epoch[261] Batch[1100] Loss[2.028] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[1100] rmse=0.017278 lr=0.000974 +[1,0]:INFO:root:Epoch[261] Batch[1200] Loss[2.116] +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[1200] rmse=0.017285 lr=0.000956 +[1,0]:INFO:root:Epoch[261] Rank[0] Batch[1251] Time cost=399.11 Train-metric=0.017281 +[1,0]:INFO:root:Epoch[261] Speed: 3209.69 samples/sec +[1,0]:INFO:root:Epoch[262] Batch[100] Loss[2.061] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[100] rmse=0.017392 lr=0.000928 +[1,0]:INFO:root:Epoch[262] Batch[200] Loss[2.189] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[200] rmse=0.017346 lr=0.000910 +[1,0]:INFO:root:Epoch[262] Batch[300] Loss[2.586] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[300] rmse=0.017314 lr=0.000892 +[1,0]:INFO:root:Epoch[262] Batch[400] Loss[2.187] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[400] rmse=0.017283 lr=0.000874 +[1,0]:INFO:root:Epoch[262] Batch[500] Loss[2.230] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[500] rmse=0.017270 lr=0.000857 +[1,0]:INFO:root:Epoch[262] Batch[600] Loss[3.939] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[600] rmse=0.017289 lr=0.000839 +[1,0]:INFO:root:Epoch[262] Batch[700] Loss[2.251] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[700] rmse=0.017277 lr=0.000822 +[1,0]:INFO:root:Epoch[262] Batch[800] Loss[2.814] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[800] rmse=0.017263 lr=0.000805 +[1,0]:INFO:root:Epoch[262] Batch[900] Loss[2.174] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[900] rmse=0.017254 lr=0.000788 +[1,0]:INFO:root:Epoch[262] Batch[1000] Loss[4.750] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[1000] rmse=0.017263 lr=0.000771 +[1,0]:INFO:root:Epoch[262] Batch[1100] Loss[4.676] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[1100] rmse=0.017274 lr=0.000755 +[1,0]:INFO:root:Epoch[262] Batch[1200] Loss[2.178] +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[1200] rmse=0.017275 lr=0.000738 +[1,0]:INFO:root:Epoch[262] Rank[0] Batch[1251] Time cost=399.46 Train-metric=0.017265 +[1,0]:INFO:root:Epoch[262] Speed: 3206.91 samples/sec +[1,0]:INFO:root:Epoch[263] Batch[100] Loss[3.285] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[100] rmse=0.017157 lr=0.000714 +[1,0]:INFO:root:Epoch[263] Batch[200] Loss[2.494] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[200] rmse=0.017251 lr=0.000698 +[1,0]:INFO:root:Epoch[263] Batch[300] Loss[2.724] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[300] rmse=0.017232 lr=0.000682 +[1,0]:INFO:root:Epoch[263] Batch[400] Loss[2.710] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[400] rmse=0.017264 lr=0.000667 +[1,0]:INFO:root:Epoch[263] Batch[500] Loss[4.703] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[500] rmse=0.017247 lr=0.000652 +[1,0]:INFO:root:Epoch[263] Batch[600] Loss[2.103] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[600] rmse=0.017217 lr=0.000636 +[1,0]:INFO:root:Epoch[263] Batch[700] Loss[1.953] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[700] rmse=0.017233 lr=0.000621 +[1,0]:INFO:root:Epoch[263] Batch[800] Loss[1.983] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[800] rmse=0.017246 lr=0.000607 +[1,0]:INFO:root:Epoch[263] Batch[900] Loss[2.076] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[900] rmse=0.017235 lr=0.000592 +[1,0]:INFO:root:Epoch[263] Batch[1000] Loss[2.210] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[1000] rmse=0.017234 lr=0.000577 +[1,0]:INFO:root:Epoch[263] Batch[1100] Loss[3.337] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[1100] rmse=0.017238 lr=0.000563 +[1,0]:INFO:root:Epoch[263] Batch[1200] Loss[1.998] +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[1200] rmse=0.017236 lr=0.000549 +[1,0]:INFO:root:Epoch[263] Rank[0] Batch[1251] Time cost=399.22 Train-metric=0.017238 +[1,0]:INFO:root:Epoch[263] Speed: 3208.81 samples/sec +[1,0]:INFO:root:Epoch[264] Batch[100] Loss[1.807] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[100] rmse=0.017111 lr=0.000528 +[1,0]:INFO:root:Epoch[264] Batch[200] Loss[1.874] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[200] rmse=0.017206 lr=0.000514 +[1,0]:INFO:root:Epoch[264] Batch[300] Loss[2.982] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[300] rmse=0.017207 lr=0.000501 +[1,0]:INFO:root:Epoch[264] Batch[400] Loss[2.172] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[400] rmse=0.017216 lr=0.000488 +[1,0]:INFO:root:Epoch[264] Batch[500] Loss[3.567] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[500] rmse=0.017199 lr=0.000474 +[1,0]:INFO:root:Epoch[264] Batch[600] Loss[4.602] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[600] rmse=0.017211 lr=0.000462 +[1,0]:INFO:root:Epoch[264] Batch[700] Loss[2.183] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[700] rmse=0.017221 lr=0.000449 +[1,0]:INFO:root:Epoch[264] Batch[800] Loss[3.683] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[800] rmse=0.017220 lr=0.000436 +[1,0]:INFO:root:Epoch[264] Batch[900] Loss[2.132] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[900] rmse=0.017213 lr=0.000424 +[1,0]:INFO:root:Epoch[264] Batch[1000] Loss[1.931] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[1000] rmse=0.017227 lr=0.000412 +[1,0]:INFO:root:Epoch[264] Batch[1100] Loss[2.603] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[1100] rmse=0.017243 lr=0.000399 +[1,0]:INFO:root:Epoch[264] Batch[1200] Loss[2.060] +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[1200] rmse=0.017248 lr=0.000388 +[1,0]:INFO:root:Epoch[264] Rank[0] Batch[1251] Time cost=398.85 Train-metric=0.017253 +[1,0]:INFO:root:Epoch[264] Speed: 3211.76 samples/sec +[1,0]:INFO:root:Epoch[264] Rank[0] Validation-accuracy=0.759560 Validation-top_k_accuracy_5=0.927940 +[1,0]:INFO:root:Epoch[265] Batch[100] Loss[2.259] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[100] rmse=0.017186 lr=0.000370 +[1,0]:INFO:root:Epoch[265] Batch[200] Loss[2.252] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[200] rmse=0.017275 lr=0.000359 +[1,0]:INFO:root:Epoch[265] Batch[300] Loss[2.079] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[300] rmse=0.017283 lr=0.000347 +[1,0]:INFO:root:Epoch[265] Batch[400] Loss[2.032] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[400] rmse=0.017280 lr=0.000336 +[1,0]:INFO:root:Epoch[265] Batch[500] Loss[1.969] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[500] rmse=0.017274 lr=0.000325 +[1,0]:INFO:root:Epoch[265] Batch[600] Loss[3.110] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[600] rmse=0.017254 lr=0.000315 +[1,0]:INFO:root:Epoch[265] Batch[700] Loss[3.185] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[700] rmse=0.017246 lr=0.000304 +[1,0]:INFO:root:Epoch[265] Batch[800] Loss[3.282] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[800] rmse=0.017252 lr=0.000294 +[1,0]:INFO:root:Epoch[265] Batch[900] Loss[2.712] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[900] rmse=0.017244 lr=0.000284 +[1,0]:INFO:root:Epoch[265] Batch[1000] Loss[4.557] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[1000] rmse=0.017237 lr=0.000274 +[1,0]:INFO:root:Epoch[265] Batch[1100] Loss[3.566] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[1100] rmse=0.017237 lr=0.000264 +[1,0]:INFO:root:Epoch[265] Batch[1200] Loss[2.197] +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[1200] rmse=0.017242 lr=0.000254 +[1,0]:INFO:root:Epoch[265] Rank[0] Batch[1251] Time cost=398.55 Train-metric=0.017246 +[1,0]:INFO:root:Epoch[265] Speed: 3214.21 samples/sec +[1,0]:INFO:root:Epoch[266] Batch[100] Loss[2.410] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[100] rmse=0.017238 lr=0.000240 +[1,0]:INFO:root:Epoch[266] Batch[200] Loss[3.596] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[200] rmse=0.017308 lr=0.000231 +[1,0]:INFO:root:Epoch[266] Batch[300] Loss[2.095] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[300] rmse=0.017271 lr=0.000222 +[1,0]:INFO:root:Epoch[266] Batch[400] Loss[3.398] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[400] rmse=0.017260 lr=0.000213 +[1,0]:INFO:root:Epoch[266] Batch[500] Loss[2.831] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[500] rmse=0.017237 lr=0.000204 +[1,0]:INFO:root:Epoch[266] Batch[600] Loss[4.693] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[600] rmse=0.017216 lr=0.000196 +[1,0]:INFO:root:Epoch[266] Batch[700] Loss[3.093] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[700] rmse=0.017203 lr=0.000188 +[1,0]:INFO:root:Epoch[266] Batch[800] Loss[2.260] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[800] rmse=0.017210 lr=0.000179 +[1,0]:INFO:root:Epoch[266] Batch[900] Loss[2.040] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[900] rmse=0.017220 lr=0.000172 +[1,0]:INFO:root:Epoch[266] Batch[1000] Loss[2.088] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[1000] rmse=0.017223 lr=0.000164 +[1,0]:INFO:root:Epoch[266] Batch[1100] Loss[2.266] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[1100] rmse=0.017212 lr=0.000156 +[1,0]:INFO:root:Epoch[266] Batch[1200] Loss[4.662] +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[1200] rmse=0.017205 lr=0.000149 +[1,0]:INFO:root:Epoch[266] Rank[0] Batch[1251] Time cost=398.88 Train-metric=0.017203 +[1,0]:INFO:root:Epoch[266] Speed: 3211.55 samples/sec +[1,0]:INFO:root:Epoch[267] Batch[100] Loss[2.142] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[100] rmse=0.017330 lr=0.000138 +[1,0]:INFO:root:Epoch[267] Batch[200] Loss[1.857] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[200] rmse=0.017212 lr=0.000131 +[1,0]:INFO:root:Epoch[267] Batch[300] Loss[3.076] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[300] rmse=0.017172 lr=0.000124 +[1,0]:INFO:root:Epoch[267] Batch[400] Loss[2.034] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[400] rmse=0.017185 lr=0.000118 +[1,0]:INFO:root:Epoch[267] Batch[500] Loss[2.032] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[500] rmse=0.017182 lr=0.000111 +[1,0]:INFO:root:Epoch[267] Batch[600] Loss[2.754] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[600] rmse=0.017185 lr=0.000105 +[1,0]:INFO:root:Epoch[267] Batch[700] Loss[4.571] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[700] rmse=0.017193 lr=0.000099 +[1,0]:INFO:root:Epoch[267] Batch[800] Loss[2.124] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[800] rmse=0.017180 lr=0.000093 +[1,0]:INFO:root:Epoch[267] Batch[900] Loss[2.436] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[900] rmse=0.017173 lr=0.000087 +[1,0]:INFO:root:Epoch[267] Batch[1000] Loss[3.540] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[1000] rmse=0.017188 lr=0.000082 +[1,0]:INFO:root:Epoch[267] Batch[1100] Loss[3.839] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[1100] rmse=0.017187 lr=0.000077 +[1,0]:INFO:root:Epoch[267] Batch[1200] Loss[2.366] +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[1200] rmse=0.017203 lr=0.000071 +[1,0]:INFO:root:Epoch[267] Rank[0] Batch[1251] Time cost=398.63 Train-metric=0.017211 +[1,0]:INFO:root:Epoch[267] Speed: 3213.53 samples/sec +[1,0]:INFO:root:Epoch[268] Batch[100] Loss[2.768] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[100] rmse=0.017178 lr=0.000064 +[1,0]:INFO:root:Epoch[268] Batch[200] Loss[3.630] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[200] rmse=0.017172 lr=0.000059 +[1,0]:INFO:root:Epoch[268] Batch[300] Loss[2.170] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[300] rmse=0.017263 lr=0.000055 +[1,0]:INFO:root:Epoch[268] Batch[400] Loss[2.091] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[400] rmse=0.017265 lr=0.000050 +[1,0]:INFO:root:Epoch[268] Batch[500] Loss[3.077] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[500] rmse=0.017262 lr=0.000046 +[1,0]:INFO:root:Epoch[268] Batch[600] Loss[2.144] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[600] rmse=0.017264 lr=0.000042 +[1,0]:INFO:root:Epoch[268] Batch[700] Loss[2.206] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[700] rmse=0.017242 lr=0.000038 +[1,0]:INFO:root:Epoch[268] Batch[800] Loss[4.643] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[800] rmse=0.017227 lr=0.000035 +[1,0]:INFO:root:Epoch[268] Batch[900] Loss[2.754] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[900] rmse=0.017204 lr=0.000031 +[1,0]:INFO:root:Epoch[268] Batch[1000] Loss[2.844] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[1000] rmse=0.017193 lr=0.000028 +[1,0]:INFO:root:Epoch[268] Batch[1100] Loss[3.554] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[1100] rmse=0.017198 lr=0.000025 +[1,0]:INFO:root:Epoch[268] Batch[1200] Loss[2.405] +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[1200] rmse=0.017200 lr=0.000022 +[1,0]:INFO:root:Epoch[268] Rank[0] Batch[1251] Time cost=398.52 Train-metric=0.017194 +[1,0]:INFO:root:Epoch[268] Speed: 3214.46 samples/sec +[1,0]:INFO:root:Epoch[269] Batch[100] Loss[2.272] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[100] rmse=0.017212 lr=0.000018 +[1,0]:INFO:root:Epoch[269] Batch[200] Loss[4.211] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[200] rmse=0.017199 lr=0.000016 +[1,0]:INFO:root:Epoch[269] Batch[300] Loss[2.316] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[300] rmse=0.017238 lr=0.000013 +[1,0]:INFO:root:Epoch[269] Batch[400] Loss[2.176] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[400] rmse=0.017195 lr=0.000011 +[1,0]:INFO:root:Epoch[269] Batch[500] Loss[4.696] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[500] rmse=0.017196 lr=0.000009 +[1,0]:INFO:root:Epoch[269] Batch[600] Loss[2.015] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[600] rmse=0.017202 lr=0.000008 +[1,0]:INFO:root:Epoch[269] Batch[700] Loss[4.063] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[700] rmse=0.017215 lr=0.000006 +[1,0]:INFO:root:Epoch[269] Batch[800] Loss[2.406] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[800] rmse=0.017213 lr=0.000005 +[1,0]:INFO:root:Epoch[269] Batch[900] Loss[4.529] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[900] rmse=0.017206 lr=0.000003 +[1,0]:INFO:root:Epoch[269] Batch[1000] Loss[2.900] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[1000] rmse=0.017191 lr=0.000002 +[1,0]:INFO:root:Epoch[269] Batch[1100] Loss[2.220] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[1100] rmse=0.017193 lr=0.000002 +[1,0]:INFO:root:Epoch[269] Batch[1200] Loss[2.029] +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[1200] rmse=0.017185 lr=0.000001 +[1,0]:INFO:root:Epoch[269] Rank[0] Batch[1251] Time cost=399.55 Train-metric=0.017193 +[1,0]:INFO:root:Epoch[269] Speed: 3206.17 samples/sec +[1,0]:INFO:root:Epoch[269] Rank[0] Validation-accuracy=0.758760 Validation-top_k_accuracy_5=0.927580 +[1,0]:INFO:root:Epoch[269] Rank[0] Validation-accuracy=0.758760 Validation-top_k_accuracy_5=0.927580 diff --git a/gluoncv/logs/classification/imagenet/resnest14.sh b/gluoncv/logs/classification/imagenet/resnest14.sh new file mode 100644 index 000000000..3242c2cce --- /dev/null +++ b/gluoncv/logs/classification/imagenet/resnest14.sh @@ -0,0 +1 @@ +horovodrun -np 8 -H localhost:8 python train_horovod.py --rec-train /home/ubuntu/data/ILSVRC2012/train.rec --rec-val /home/ubuntu/data/ILSVRC2012/val.rec --model resnest14 --lr 0.05 --num-epochs 270 --batch-size 128 --use-rec --dtype float32 --warmup-epochs 5 --last-gamma --no-wd --label-smoothing --mixup --save-dir params_resnest14 --log-interval 100 --eval-frequency 5 --auto_aug --input-size 224 --data-nthreads 10 \ No newline at end of file From c12bac75d0d3d87cd9fe84b31301bc50036aa75f Mon Sep 17 00:00:00 2001 From: Jerry Zhang Date: Mon, 4 May 2020 15:45:08 -0700 Subject: [PATCH 2/2] faster rcnn resnest269 --- .../faster_rcnn_fpn_syncbn_resnest269_coco.sh | 1 + ..._rcnn_fpn_syncbn_resnest269_coco_train.log | 6375 +++++++++++++++++ 2 files changed, 6376 insertions(+) create mode 100644 gluoncv/logs/detection/faster_rcnn_fpn_syncbn_resnest269_coco.sh create mode 100644 gluoncv/logs/detection/faster_rcnn_fpn_syncbn_resnest269_coco_train.log diff --git a/gluoncv/logs/detection/faster_rcnn_fpn_syncbn_resnest269_coco.sh b/gluoncv/logs/detection/faster_rcnn_fpn_syncbn_resnest269_coco.sh new file mode 100644 index 000000000..5184d2074 --- /dev/null +++ b/gluoncv/logs/detection/faster_rcnn_fpn_syncbn_resnest269_coco.sh @@ -0,0 +1 @@ +python train_faster_rcnn.py --gpus 0,1,2,3,4,5,6,7 --dataset coco --batch-size 8 --use-fpn --lr 0.01 --lr-warmup 1000 --rpn-smoothl1-rho 0.001 --rcnn-smoothl1-rho 0.001 -j16 --network resnest269 --executor-threads 8 --val-interval 1 --epochs 26 --lr-decay-epoch 20,24 --lr-warmup-factor 0.3333 --norm-layer syncbn --disable-hybridization diff --git a/gluoncv/logs/detection/faster_rcnn_fpn_syncbn_resnest269_coco_train.log b/gluoncv/logs/detection/faster_rcnn_fpn_syncbn_resnest269_coco_train.log new file mode 100644 index 000000000..6e1de9271 --- /dev/null +++ b/gluoncv/logs/detection/faster_rcnn_fpn_syncbn_resnest269_coco_train.log @@ -0,0 +1,6375 @@ +Namespace(amp=False, batch_size=16, custom_model=None, dataset='coco', disable_hybridization=True, epochs=26, executor_threads=8, gpus='0,1,2,3,4,5,6,7', horovod=False, kv_store='nccl', log_interval=100, lr=0.02, lr_decay=0.1, lr_decay_epoch='20,24', lr_warmup='500', lr_warmup_factor=0.3333, mixup=False, momentum=0.9, network='resnest269', no_mixup_epochs=20, norm_layer='syncbn', num_workers=16, rcnn_smoothl1_rho=0.001, resume='', rpn_smoothl1_rho=0.001, save_interval=1, save_prefix='faster_rcnn_fpn_syncbn_resnest269_coco', seed=233, start_epoch=0, static_alloc=False, use_fpn=True, val_interval=1, verbose=False, wd=0.0001) +Start training from [Epoch 0] +[Epoch 0 Iteration 0] Set learning rate to 0.006666 +Namespace(amp=False, batch_size=8, custom_model=None, dataset='coco', disable_hybridization=True, epochs=26, executor_threads=8, gpus='0,1,2,3,4,5,6,7', horovod=False, kv_store='nccl', log_interval=100, lr=0.01, lr_decay=0.1, lr_decay_epoch='20,24', lr_warmup='1000', lr_warmup_factor=0.3333, mixup=False, momentum=0.9, network='resnest269', no_mixup_epochs=20, norm_layer='syncbn', num_workers=16, rcnn_smoothl1_rho=0.001, resume='', rpn_smoothl1_rho=0.001, save_interval=1, save_prefix='faster_rcnn_fpn_syncbn_resnest269_coco', seed=233, start_epoch=0, static_alloc=False, use_fpn=True, val_interval=1, verbose=False, wd=0.0001) +Start training from [Epoch 0] +[Epoch 0 Iteration 0] Set learning rate to 0.003333 +[Epoch 0][Batch 99], Speed: 5.272 samples/sec, RPN_Conf=0.443,RPN_SmoothL1=0.084,RCNN_CrossEntropy=0.475,RCNN_SmoothL1=0.073,RPNAcc=0.862,RPNL1Loss=0.584,RCNNAcc=0.959,RCNNL1Loss=1.536 +[Epoch 0 Iteration 100] Set learning rate to 0.0039997 +[Epoch 0][Batch 199], Speed: 6.684 samples/sec, RPN_Conf=0.352,RPN_SmoothL1=0.086,RCNN_CrossEntropy=0.450,RCNN_SmoothL1=0.148,RPNAcc=0.872,RPNL1Loss=0.574,RCNNAcc=0.947,RCNNL1Loss=1.957 +[Epoch 0 Iteration 200] Set learning rate to 0.0046664 +[Epoch 0][Batch 299], Speed: 6.639 samples/sec, RPN_Conf=0.295,RPN_SmoothL1=0.087,RCNN_CrossEntropy=0.475,RCNN_SmoothL1=0.201,RPNAcc=0.874,RPNL1Loss=0.566,RCNNAcc=0.937,RCNNL1Loss=2.114 +[Epoch 0 Iteration 300] Set learning rate to 0.0053330999999999995 +[Epoch 0][Batch 399], Speed: 6.158 samples/sec, RPN_Conf=0.260,RPN_SmoothL1=0.086,RCNN_CrossEntropy=0.482,RCNN_SmoothL1=0.231,RPNAcc=0.877,RPNL1Loss=0.565,RCNNAcc=0.932,RCNNL1Loss=2.183 +[Epoch 0 Iteration 400] Set learning rate to 0.0059998 +[Epoch 0][Batch 499], Speed: 6.611 samples/sec, RPN_Conf=0.237,RPN_SmoothL1=0.087,RCNN_CrossEntropy=0.485,RCNN_SmoothL1=0.250,RPNAcc=0.880,RPNL1Loss=0.564,RCNNAcc=0.928,RCNNL1Loss=2.210 +[Epoch 0 Iteration 500] Set learning rate to 0.0066665 +[Epoch 0][Batch 599], Speed: 6.650 samples/sec, RPN_Conf=0.220,RPN_SmoothL1=0.087,RCNN_CrossEntropy=0.484,RCNN_SmoothL1=0.262,RPNAcc=0.888,RPNL1Loss=0.562,RCNNAcc=0.926,RCNNL1Loss=2.220 +[Epoch 0 Iteration 600] Set learning rate to 0.0073332 +[Epoch 0][Batch 699], Speed: 6.514 samples/sec, RPN_Conf=0.207,RPN_SmoothL1=0.086,RCNN_CrossEntropy=0.480,RCNN_SmoothL1=0.267,RPNAcc=0.898,RPNL1Loss=0.557,RCNNAcc=0.925,RCNNL1Loss=2.214 +[Epoch 0 Iteration 700] Set learning rate to 0.0079999 +[Epoch 0][Batch 799], Speed: 6.120 samples/sec, RPN_Conf=0.195,RPN_SmoothL1=0.087,RCNN_CrossEntropy=0.476,RCNN_SmoothL1=0.273,RPNAcc=0.906,RPNL1Loss=0.556,RCNNAcc=0.924,RCNNL1Loss=2.207 +[Epoch 0 Iteration 800] Set learning rate to 0.0086666 +[Epoch 0][Batch 899], Speed: 6.283 samples/sec, RPN_Conf=0.184,RPN_SmoothL1=0.086,RCNN_CrossEntropy=0.478,RCNN_SmoothL1=0.284,RPNAcc=0.912,RPNL1Loss=0.551,RCNNAcc=0.922,RCNNL1Loss=2.200 +[Epoch 0 Iteration 900] Set learning rate to 0.009333300000000001 +[Epoch 0][Batch 999], Speed: 5.779 samples/sec, RPN_Conf=0.173,RPN_SmoothL1=0.085,RCNN_CrossEntropy=0.478,RCNN_SmoothL1=0.293,RPNAcc=0.918,RPNL1Loss=0.547,RCNNAcc=0.920,RCNNL1Loss=2.185 +[Epoch 0 Iteration 1000] Set learning rate to 0.01 +[Epoch 0][Batch 1099], Speed: 6.093 samples/sec, RPN_Conf=0.164,RPN_SmoothL1=0.084,RCNN_CrossEntropy=0.476,RCNN_SmoothL1=0.299,RPNAcc=0.923,RPNL1Loss=0.544,RCNNAcc=0.918,RCNNL1Loss=2.169 +[Epoch 0][Batch 1199], Speed: 6.350 samples/sec, RPN_Conf=0.157,RPN_SmoothL1=0.084,RCNN_CrossEntropy=0.474,RCNN_SmoothL1=0.304,RPNAcc=0.927,RPNL1Loss=0.539,RCNNAcc=0.917,RCNNL1Loss=2.146 +[Epoch 0][Batch 1299], Speed: 5.709 samples/sec, RPN_Conf=0.151,RPN_SmoothL1=0.083,RCNN_CrossEntropy=0.476,RCNN_SmoothL1=0.312,RPNAcc=0.930,RPNL1Loss=0.534,RCNNAcc=0.915,RCNNL1Loss=2.119 +[Epoch 0][Batch 1399], Speed: 6.008 samples/sec, RPN_Conf=0.145,RPN_SmoothL1=0.083,RCNN_CrossEntropy=0.476,RCNN_SmoothL1=0.318,RPNAcc=0.933,RPNL1Loss=0.529,RCNNAcc=0.914,RCNNL1Loss=2.092 +[Epoch 0][Batch 1499], Speed: 6.350 samples/sec, RPN_Conf=0.139,RPN_SmoothL1=0.082,RCNN_CrossEntropy=0.474,RCNN_SmoothL1=0.321,RPNAcc=0.936,RPNL1Loss=0.525,RCNNAcc=0.913,RCNNL1Loss=2.062 +[Epoch 0][Batch 1599], Speed: 6.089 samples/sec, RPN_Conf=0.135,RPN_SmoothL1=0.081,RCNN_CrossEntropy=0.472,RCNN_SmoothL1=0.324,RPNAcc=0.939,RPNL1Loss=0.520,RCNNAcc=0.912,RCNNL1Loss=2.035 +[Epoch 0][Batch 1699], Speed: 6.712 samples/sec, RPN_Conf=0.130,RPN_SmoothL1=0.081,RCNN_CrossEntropy=0.469,RCNN_SmoothL1=0.326,RPNAcc=0.941,RPNL1Loss=0.515,RCNNAcc=0.912,RCNNL1Loss=2.005 +[Epoch 0][Batch 1799], Speed: 6.262 samples/sec, RPN_Conf=0.127,RPN_SmoothL1=0.080,RCNN_CrossEntropy=0.467,RCNN_SmoothL1=0.329,RPNAcc=0.943,RPNL1Loss=0.511,RCNNAcc=0.911,RCNNL1Loss=1.977 +[Epoch 0][Batch 1899], Speed: 6.155 samples/sec, RPN_Conf=0.123,RPN_SmoothL1=0.080,RCNN_CrossEntropy=0.465,RCNN_SmoothL1=0.331,RPNAcc=0.945,RPNL1Loss=0.507,RCNNAcc=0.910,RCNNL1Loss=1.950 +[Epoch 0][Batch 1999], Speed: 6.226 samples/sec, RPN_Conf=0.120,RPN_SmoothL1=0.080,RCNN_CrossEntropy=0.462,RCNN_SmoothL1=0.333,RPNAcc=0.946,RPNL1Loss=0.503,RCNNAcc=0.909,RCNNL1Loss=1.924 +[Epoch 0][Batch 2099], Speed: 5.660 samples/sec, RPN_Conf=0.117,RPN_SmoothL1=0.079,RCNN_CrossEntropy=0.460,RCNN_SmoothL1=0.335,RPNAcc=0.948,RPNL1Loss=0.498,RCNNAcc=0.909,RCNNL1Loss=1.900 +[Epoch 0][Batch 2199], Speed: 5.776 samples/sec, RPN_Conf=0.115,RPN_SmoothL1=0.079,RCNN_CrossEntropy=0.457,RCNN_SmoothL1=0.336,RPNAcc=0.949,RPNL1Loss=0.494,RCNNAcc=0.908,RCNNL1Loss=1.876 +[Epoch 0][Batch 2299], Speed: 6.254 samples/sec, RPN_Conf=0.112,RPN_SmoothL1=0.078,RCNN_CrossEntropy=0.454,RCNN_SmoothL1=0.337,RPNAcc=0.950,RPNL1Loss=0.490,RCNNAcc=0.907,RCNNL1Loss=1.852 +[Epoch 0][Batch 2399], Speed: 5.971 samples/sec, RPN_Conf=0.110,RPN_SmoothL1=0.078,RCNN_CrossEntropy=0.451,RCNN_SmoothL1=0.338,RPNAcc=0.951,RPNL1Loss=0.487,RCNNAcc=0.907,RCNNL1Loss=1.832 +[Epoch 0][Batch 2499], Speed: 6.054 samples/sec, RPN_Conf=0.108,RPN_SmoothL1=0.078,RCNN_CrossEntropy=0.449,RCNN_SmoothL1=0.339,RPNAcc=0.952,RPNL1Loss=0.484,RCNNAcc=0.907,RCNNL1Loss=1.810 +[Epoch 0][Batch 2599], Speed: 6.078 samples/sec, RPN_Conf=0.106,RPN_SmoothL1=0.077,RCNN_CrossEntropy=0.446,RCNN_SmoothL1=0.339,RPNAcc=0.953,RPNL1Loss=0.481,RCNNAcc=0.906,RCNNL1Loss=1.791 +[Epoch 0][Batch 2699], Speed: 6.308 samples/sec, RPN_Conf=0.104,RPN_SmoothL1=0.077,RCNN_CrossEntropy=0.443,RCNN_SmoothL1=0.339,RPNAcc=0.954,RPNL1Loss=0.478,RCNNAcc=0.906,RCNNL1Loss=1.772 +[Epoch 0][Batch 2799], Speed: 5.745 samples/sec, RPN_Conf=0.103,RPN_SmoothL1=0.076,RCNN_CrossEntropy=0.440,RCNN_SmoothL1=0.340,RPNAcc=0.955,RPNL1Loss=0.475,RCNNAcc=0.906,RCNNL1Loss=1.754 +[Epoch 0][Batch 2899], Speed: 5.611 samples/sec, RPN_Conf=0.101,RPN_SmoothL1=0.076,RCNN_CrossEntropy=0.437,RCNN_SmoothL1=0.340,RPNAcc=0.956,RPNL1Loss=0.472,RCNNAcc=0.906,RCNNL1Loss=1.736 +[Epoch 0][Batch 2999], Speed: 6.192 samples/sec, RPN_Conf=0.099,RPN_SmoothL1=0.076,RCNN_CrossEntropy=0.435,RCNN_SmoothL1=0.340,RPNAcc=0.957,RPNL1Loss=0.469,RCNNAcc=0.906,RCNNL1Loss=1.720 +[Epoch 0][Batch 3099], Speed: 5.931 samples/sec, RPN_Conf=0.098,RPN_SmoothL1=0.075,RCNN_CrossEntropy=0.432,RCNN_SmoothL1=0.340,RPNAcc=0.958,RPNL1Loss=0.466,RCNNAcc=0.906,RCNNL1Loss=1.702 +[Epoch 0][Batch 3199], Speed: 6.047 samples/sec, RPN_Conf=0.096,RPN_SmoothL1=0.075,RCNN_CrossEntropy=0.429,RCNN_SmoothL1=0.340,RPNAcc=0.958,RPNL1Loss=0.464,RCNNAcc=0.906,RCNNL1Loss=1.686 +[Epoch 0][Batch 3299], Speed: 5.341 samples/sec, RPN_Conf=0.095,RPN_SmoothL1=0.074,RCNN_CrossEntropy=0.426,RCNN_SmoothL1=0.339,RPNAcc=0.959,RPNL1Loss=0.461,RCNNAcc=0.906,RCNNL1Loss=1.672 +[Epoch 0][Batch 3399], Speed: 5.647 samples/sec, RPN_Conf=0.094,RPN_SmoothL1=0.074,RCNN_CrossEntropy=0.423,RCNN_SmoothL1=0.339,RPNAcc=0.960,RPNL1Loss=0.459,RCNNAcc=0.906,RCNNL1Loss=1.658 +[Epoch 0][Batch 3499], Speed: 6.143 samples/sec, RPN_Conf=0.093,RPN_SmoothL1=0.074,RCNN_CrossEntropy=0.420,RCNN_SmoothL1=0.339,RPNAcc=0.960,RPNL1Loss=0.457,RCNNAcc=0.906,RCNNL1Loss=1.643 +[Epoch 0][Batch 3599], Speed: 5.332 samples/sec, RPN_Conf=0.091,RPN_SmoothL1=0.074,RCNN_CrossEntropy=0.418,RCNN_SmoothL1=0.339,RPNAcc=0.961,RPNL1Loss=0.454,RCNNAcc=0.906,RCNNL1Loss=1.630 +[Epoch 0][Batch 3699], Speed: 6.238 samples/sec, RPN_Conf=0.090,RPN_SmoothL1=0.073,RCNN_CrossEntropy=0.415,RCNN_SmoothL1=0.338,RPNAcc=0.961,RPNL1Loss=0.452,RCNNAcc=0.906,RCNNL1Loss=1.618 +[Epoch 0][Batch 3799], Speed: 5.762 samples/sec, RPN_Conf=0.090,RPN_SmoothL1=0.073,RCNN_CrossEntropy=0.413,RCNN_SmoothL1=0.338,RPNAcc=0.962,RPNL1Loss=0.450,RCNNAcc=0.906,RCNNL1Loss=1.606 +[Epoch 0][Batch 3899], Speed: 5.884 samples/sec, RPN_Conf=0.089,RPN_SmoothL1=0.073,RCNN_CrossEntropy=0.410,RCNN_SmoothL1=0.338,RPNAcc=0.962,RPNL1Loss=0.448,RCNNAcc=0.906,RCNNL1Loss=1.594 +[Epoch 0][Batch 3999], Speed: 5.814 samples/sec, RPN_Conf=0.088,RPN_SmoothL1=0.073,RCNN_CrossEntropy=0.408,RCNN_SmoothL1=0.338,RPNAcc=0.963,RPNL1Loss=0.446,RCNNAcc=0.906,RCNNL1Loss=1.582 +[Epoch 0][Batch 4099], Speed: 6.285 samples/sec, RPN_Conf=0.087,RPN_SmoothL1=0.072,RCNN_CrossEntropy=0.406,RCNN_SmoothL1=0.338,RPNAcc=0.963,RPNL1Loss=0.444,RCNNAcc=0.906,RCNNL1Loss=1.571 +[Epoch 0][Batch 4199], Speed: 5.866 samples/sec, RPN_Conf=0.086,RPN_SmoothL1=0.072,RCNN_CrossEntropy=0.404,RCNN_SmoothL1=0.338,RPNAcc=0.964,RPNL1Loss=0.443,RCNNAcc=0.906,RCNNL1Loss=1.561 +[Epoch 0][Batch 4299], Speed: 6.193 samples/sec, RPN_Conf=0.085,RPN_SmoothL1=0.072,RCNN_CrossEntropy=0.401,RCNN_SmoothL1=0.337,RPNAcc=0.964,RPNL1Loss=0.441,RCNNAcc=0.906,RCNNL1Loss=1.551 +[Epoch 0][Batch 4399], Speed: 6.258 samples/sec, RPN_Conf=0.084,RPN_SmoothL1=0.072,RCNN_CrossEntropy=0.398,RCNN_SmoothL1=0.336,RPNAcc=0.964,RPNL1Loss=0.440,RCNNAcc=0.906,RCNNL1Loss=1.542 +[Epoch 0][Batch 4499], Speed: 5.758 samples/sec, RPN_Conf=0.084,RPN_SmoothL1=0.071,RCNN_CrossEntropy=0.397,RCNN_SmoothL1=0.337,RPNAcc=0.965,RPNL1Loss=0.438,RCNNAcc=0.906,RCNNL1Loss=1.532 +[Epoch 0][Batch 4599], Speed: 6.205 samples/sec, RPN_Conf=0.083,RPN_SmoothL1=0.071,RCNN_CrossEntropy=0.395,RCNN_SmoothL1=0.336,RPNAcc=0.965,RPNL1Loss=0.436,RCNNAcc=0.906,RCNNL1Loss=1.523 +[Epoch 0][Batch 4699], Speed: 6.260 samples/sec, RPN_Conf=0.082,RPN_SmoothL1=0.071,RCNN_CrossEntropy=0.393,RCNN_SmoothL1=0.336,RPNAcc=0.965,RPNL1Loss=0.435,RCNNAcc=0.907,RCNNL1Loss=1.515 +[Epoch 0][Batch 4799], Speed: 6.125 samples/sec, RPN_Conf=0.082,RPN_SmoothL1=0.071,RCNN_CrossEntropy=0.391,RCNN_SmoothL1=0.336,RPNAcc=0.966,RPNL1Loss=0.433,RCNNAcc=0.907,RCNNL1Loss=1.508 +[Epoch 0][Batch 4899], Speed: 5.989 samples/sec, RPN_Conf=0.081,RPN_SmoothL1=0.071,RCNN_CrossEntropy=0.390,RCNN_SmoothL1=0.336,RPNAcc=0.966,RPNL1Loss=0.431,RCNNAcc=0.907,RCNNL1Loss=1.499 +[Epoch 0][Batch 4999], Speed: 6.141 samples/sec, RPN_Conf=0.081,RPN_SmoothL1=0.071,RCNN_CrossEntropy=0.388,RCNN_SmoothL1=0.336,RPNAcc=0.966,RPNL1Loss=0.430,RCNNAcc=0.907,RCNNL1Loss=1.491 +[Epoch 0][Batch 5099], Speed: 6.152 samples/sec, RPN_Conf=0.080,RPN_SmoothL1=0.070,RCNN_CrossEntropy=0.386,RCNN_SmoothL1=0.335,RPNAcc=0.967,RPNL1Loss=0.429,RCNNAcc=0.907,RCNNL1Loss=1.483 +[Epoch 0][Batch 5199], Speed: 5.367 samples/sec, RPN_Conf=0.079,RPN_SmoothL1=0.070,RCNN_CrossEntropy=0.385,RCNN_SmoothL1=0.335,RPNAcc=0.967,RPNL1Loss=0.427,RCNNAcc=0.907,RCNNL1Loss=1.476 +[Epoch 0][Batch 5299], Speed: 5.750 samples/sec, RPN_Conf=0.079,RPN_SmoothL1=0.070,RCNN_CrossEntropy=0.383,RCNN_SmoothL1=0.335,RPNAcc=0.967,RPNL1Loss=0.426,RCNNAcc=0.907,RCNNL1Loss=1.468 +[Epoch 0][Batch 5399], Speed: 5.870 samples/sec, RPN_Conf=0.078,RPN_SmoothL1=0.070,RCNN_CrossEntropy=0.382,RCNN_SmoothL1=0.335,RPNAcc=0.967,RPNL1Loss=0.424,RCNNAcc=0.907,RCNNL1Loss=1.461 +[Epoch 0][Batch 5499], Speed: 5.698 samples/sec, RPN_Conf=0.078,RPN_SmoothL1=0.070,RCNN_CrossEntropy=0.380,RCNN_SmoothL1=0.335,RPNAcc=0.968,RPNL1Loss=0.423,RCNNAcc=0.907,RCNNL1Loss=1.455 +[Epoch 0][Batch 5599], Speed: 6.203 samples/sec, RPN_Conf=0.077,RPN_SmoothL1=0.070,RCNN_CrossEntropy=0.379,RCNN_SmoothL1=0.335,RPNAcc=0.968,RPNL1Loss=0.422,RCNNAcc=0.907,RCNNL1Loss=1.448 +[Epoch 0][Batch 5699], Speed: 6.075 samples/sec, RPN_Conf=0.077,RPN_SmoothL1=0.070,RCNN_CrossEntropy=0.377,RCNN_SmoothL1=0.334,RPNAcc=0.968,RPNL1Loss=0.420,RCNNAcc=0.907,RCNNL1Loss=1.441 +[Epoch 0][Batch 5799], Speed: 5.453 samples/sec, RPN_Conf=0.076,RPN_SmoothL1=0.069,RCNN_CrossEntropy=0.376,RCNN_SmoothL1=0.334,RPNAcc=0.968,RPNL1Loss=0.419,RCNNAcc=0.907,RCNNL1Loss=1.435 +[Epoch 0][Batch 5899], Speed: 5.414 samples/sec, RPN_Conf=0.076,RPN_SmoothL1=0.069,RCNN_CrossEntropy=0.374,RCNN_SmoothL1=0.334,RPNAcc=0.969,RPNL1Loss=0.418,RCNNAcc=0.907,RCNNL1Loss=1.429 +[Epoch 0][Batch 5999], Speed: 5.688 samples/sec, RPN_Conf=0.075,RPN_SmoothL1=0.069,RCNN_CrossEntropy=0.373,RCNN_SmoothL1=0.333,RPNAcc=0.969,RPNL1Loss=0.417,RCNNAcc=0.908,RCNNL1Loss=1.423 +[Epoch 0][Batch 6099], Speed: 5.995 samples/sec, RPN_Conf=0.075,RPN_SmoothL1=0.069,RCNN_CrossEntropy=0.371,RCNN_SmoothL1=0.333,RPNAcc=0.969,RPNL1Loss=0.416,RCNNAcc=0.908,RCNNL1Loss=1.417 +[Epoch 0][Batch 6199], Speed: 6.547 samples/sec, RPN_Conf=0.074,RPN_SmoothL1=0.069,RCNN_CrossEntropy=0.370,RCNN_SmoothL1=0.333,RPNAcc=0.969,RPNL1Loss=0.415,RCNNAcc=0.908,RCNNL1Loss=1.412 +[Epoch 0][Batch 6299], Speed: 6.295 samples/sec, RPN_Conf=0.074,RPN_SmoothL1=0.068,RCNN_CrossEntropy=0.368,RCNN_SmoothL1=0.332,RPNAcc=0.969,RPNL1Loss=0.414,RCNNAcc=0.908,RCNNL1Loss=1.406 +[Epoch 0][Batch 6399], Speed: 5.664 samples/sec, RPN_Conf=0.073,RPN_SmoothL1=0.068,RCNN_CrossEntropy=0.367,RCNN_SmoothL1=0.332,RPNAcc=0.970,RPNL1Loss=0.413,RCNNAcc=0.908,RCNNL1Loss=1.401 +[Epoch 0][Batch 6499], Speed: 5.711 samples/sec, RPN_Conf=0.073,RPN_SmoothL1=0.068,RCNN_CrossEntropy=0.366,RCNN_SmoothL1=0.332,RPNAcc=0.970,RPNL1Loss=0.411,RCNNAcc=0.908,RCNNL1Loss=1.396 +[Epoch 0][Batch 6599], Speed: 5.817 samples/sec, RPN_Conf=0.073,RPN_SmoothL1=0.068,RCNN_CrossEntropy=0.364,RCNN_SmoothL1=0.331,RPNAcc=0.970,RPNL1Loss=0.410,RCNNAcc=0.908,RCNNL1Loss=1.391 +[Epoch 0][Batch 6699], Speed: 5.993 samples/sec, RPN_Conf=0.072,RPN_SmoothL1=0.068,RCNN_CrossEntropy=0.363,RCNN_SmoothL1=0.331,RPNAcc=0.970,RPNL1Loss=0.409,RCNNAcc=0.908,RCNNL1Loss=1.386 +[Epoch 0][Batch 6799], Speed: 6.133 samples/sec, RPN_Conf=0.072,RPN_SmoothL1=0.068,RCNN_CrossEntropy=0.362,RCNN_SmoothL1=0.331,RPNAcc=0.970,RPNL1Loss=0.408,RCNNAcc=0.908,RCNNL1Loss=1.381 +[Epoch 0][Batch 6899], Speed: 5.833 samples/sec, RPN_Conf=0.072,RPN_SmoothL1=0.068,RCNN_CrossEntropy=0.361,RCNN_SmoothL1=0.330,RPNAcc=0.971,RPNL1Loss=0.407,RCNNAcc=0.909,RCNNL1Loss=1.376 +[Epoch 0][Batch 6999], Speed: 5.919 samples/sec, RPN_Conf=0.071,RPN_SmoothL1=0.068,RCNN_CrossEntropy=0.359,RCNN_SmoothL1=0.330,RPNAcc=0.971,RPNL1Loss=0.406,RCNNAcc=0.909,RCNNL1Loss=1.371 +[Epoch 0][Batch 7099], Speed: 6.347 samples/sec, RPN_Conf=0.071,RPN_SmoothL1=0.067,RCNN_CrossEntropy=0.358,RCNN_SmoothL1=0.330,RPNAcc=0.971,RPNL1Loss=0.405,RCNNAcc=0.909,RCNNL1Loss=1.366 +[Epoch 0][Batch 7199], Speed: 6.003 samples/sec, RPN_Conf=0.070,RPN_SmoothL1=0.067,RCNN_CrossEntropy=0.357,RCNN_SmoothL1=0.330,RPNAcc=0.971,RPNL1Loss=0.404,RCNNAcc=0.909,RCNNL1Loss=1.361 +[Epoch 0][Batch 7299], Speed: 6.007 samples/sec, RPN_Conf=0.070,RPN_SmoothL1=0.067,RCNN_CrossEntropy=0.356,RCNN_SmoothL1=0.330,RPNAcc=0.971,RPNL1Loss=0.403,RCNNAcc=0.909,RCNNL1Loss=1.357 +[Epoch 0][Batch 7399], Speed: 5.925 samples/sec, RPN_Conf=0.070,RPN_SmoothL1=0.067,RCNN_CrossEntropy=0.355,RCNN_SmoothL1=0.329,RPNAcc=0.971,RPNL1Loss=0.402,RCNNAcc=0.909,RCNNL1Loss=1.353 +[Epoch 0][Batch 7499], Speed: 6.201 samples/sec, RPN_Conf=0.069,RPN_SmoothL1=0.067,RCNN_CrossEntropy=0.354,RCNN_SmoothL1=0.329,RPNAcc=0.972,RPNL1Loss=0.401,RCNNAcc=0.909,RCNNL1Loss=1.349 +[Epoch 0][Batch 7599], Speed: 5.913 samples/sec, RPN_Conf=0.069,RPN_SmoothL1=0.067,RCNN_CrossEntropy=0.353,RCNN_SmoothL1=0.329,RPNAcc=0.972,RPNL1Loss=0.401,RCNNAcc=0.909,RCNNL1Loss=1.345 +[Epoch 0][Batch 7699], Speed: 6.110 samples/sec, RPN_Conf=0.069,RPN_SmoothL1=0.067,RCNN_CrossEntropy=0.352,RCNN_SmoothL1=0.329,RPNAcc=0.972,RPNL1Loss=0.400,RCNNAcc=0.909,RCNNL1Loss=1.341 +[Epoch 0][Batch 7799], Speed: 6.107 samples/sec, RPN_Conf=0.069,RPN_SmoothL1=0.067,RCNN_CrossEntropy=0.351,RCNN_SmoothL1=0.328,RPNAcc=0.972,RPNL1Loss=0.399,RCNNAcc=0.909,RCNNL1Loss=1.337 +[Epoch 0][Batch 7899], Speed: 5.828 samples/sec, RPN_Conf=0.068,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.350,RCNN_SmoothL1=0.328,RPNAcc=0.972,RPNL1Loss=0.398,RCNNAcc=0.910,RCNNL1Loss=1.333 +[Epoch 0][Batch 7999], Speed: 6.232 samples/sec, RPN_Conf=0.068,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.349,RCNN_SmoothL1=0.328,RPNAcc=0.972,RPNL1Loss=0.397,RCNNAcc=0.910,RCNNL1Loss=1.329 +[Epoch 0][Batch 8099], Speed: 6.064 samples/sec, RPN_Conf=0.068,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.348,RCNN_SmoothL1=0.327,RPNAcc=0.972,RPNL1Loss=0.396,RCNNAcc=0.910,RCNNL1Loss=1.325 +[Epoch 0][Batch 8199], Speed: 6.189 samples/sec, RPN_Conf=0.067,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.347,RCNN_SmoothL1=0.327,RPNAcc=0.973,RPNL1Loss=0.395,RCNNAcc=0.910,RCNNL1Loss=1.321 +[Epoch 0][Batch 8299], Speed: 6.132 samples/sec, RPN_Conf=0.067,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.346,RCNN_SmoothL1=0.327,RPNAcc=0.973,RPNL1Loss=0.395,RCNNAcc=0.910,RCNNL1Loss=1.317 +[Epoch 0][Batch 8399], Speed: 6.004 samples/sec, RPN_Conf=0.067,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.345,RCNN_SmoothL1=0.327,RPNAcc=0.973,RPNL1Loss=0.394,RCNNAcc=0.910,RCNNL1Loss=1.313 +[Epoch 0][Batch 8499], Speed: 5.998 samples/sec, RPN_Conf=0.067,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.344,RCNN_SmoothL1=0.326,RPNAcc=0.973,RPNL1Loss=0.393,RCNNAcc=0.910,RCNNL1Loss=1.310 +[Epoch 0][Batch 8599], Speed: 6.003 samples/sec, RPN_Conf=0.066,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.343,RCNN_SmoothL1=0.326,RPNAcc=0.973,RPNL1Loss=0.392,RCNNAcc=0.910,RCNNL1Loss=1.306 +[Epoch 0][Batch 8699], Speed: 6.181 samples/sec, RPN_Conf=0.066,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.342,RCNN_SmoothL1=0.326,RPNAcc=0.973,RPNL1Loss=0.392,RCNNAcc=0.910,RCNNL1Loss=1.303 +[Epoch 0][Batch 8799], Speed: 6.004 samples/sec, RPN_Conf=0.066,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.341,RCNN_SmoothL1=0.326,RPNAcc=0.973,RPNL1Loss=0.391,RCNNAcc=0.910,RCNNL1Loss=1.300 +[Epoch 0][Batch 8899], Speed: 5.881 samples/sec, RPN_Conf=0.066,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.341,RCNN_SmoothL1=0.326,RPNAcc=0.973,RPNL1Loss=0.390,RCNNAcc=0.910,RCNNL1Loss=1.296 +[Epoch 0][Batch 8999], Speed: 6.012 samples/sec, RPN_Conf=0.066,RPN_SmoothL1=0.066,RCNN_CrossEntropy=0.340,RCNN_SmoothL1=0.326,RPNAcc=0.973,RPNL1Loss=0.389,RCNNAcc=0.910,RCNNL1Loss=1.292 +[Epoch 0][Batch 9099], Speed: 5.734 samples/sec, RPN_Conf=0.065,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.339,RCNN_SmoothL1=0.325,RPNAcc=0.974,RPNL1Loss=0.389,RCNNAcc=0.910,RCNNL1Loss=1.289 +[Epoch 0][Batch 9199], Speed: 6.218 samples/sec, RPN_Conf=0.065,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.338,RCNN_SmoothL1=0.325,RPNAcc=0.974,RPNL1Loss=0.388,RCNNAcc=0.911,RCNNL1Loss=1.286 +[Epoch 0][Batch 9299], Speed: 5.865 samples/sec, RPN_Conf=0.065,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.337,RCNN_SmoothL1=0.325,RPNAcc=0.974,RPNL1Loss=0.387,RCNNAcc=0.911,RCNNL1Loss=1.282 +[Epoch 0][Batch 9399], Speed: 5.769 samples/sec, RPN_Conf=0.065,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.337,RCNN_SmoothL1=0.325,RPNAcc=0.974,RPNL1Loss=0.387,RCNNAcc=0.911,RCNNL1Loss=1.279 +[Epoch 0][Batch 9499], Speed: 5.915 samples/sec, RPN_Conf=0.064,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.336,RCNN_SmoothL1=0.325,RPNAcc=0.974,RPNL1Loss=0.386,RCNNAcc=0.911,RCNNL1Loss=1.276 +[Epoch 0][Batch 9599], Speed: 5.785 samples/sec, RPN_Conf=0.064,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.335,RCNN_SmoothL1=0.324,RPNAcc=0.974,RPNL1Loss=0.385,RCNNAcc=0.911,RCNNL1Loss=1.273 +[Epoch 0][Batch 9699], Speed: 6.184 samples/sec, RPN_Conf=0.064,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.335,RCNN_SmoothL1=0.324,RPNAcc=0.974,RPNL1Loss=0.385,RCNNAcc=0.911,RCNNL1Loss=1.270 +[Epoch 0][Batch 9799], Speed: 6.324 samples/sec, RPN_Conf=0.064,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.334,RCNN_SmoothL1=0.324,RPNAcc=0.974,RPNL1Loss=0.384,RCNNAcc=0.911,RCNNL1Loss=1.267 +[Epoch 0][Batch 9899], Speed: 5.766 samples/sec, RPN_Conf=0.064,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.333,RCNN_SmoothL1=0.324,RPNAcc=0.974,RPNL1Loss=0.383,RCNNAcc=0.911,RCNNL1Loss=1.264 +[Epoch 0][Batch 9999], Speed: 6.035 samples/sec, RPN_Conf=0.064,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.332,RCNN_SmoothL1=0.324,RPNAcc=0.974,RPNL1Loss=0.383,RCNNAcc=0.911,RCNNL1Loss=1.262 +[Epoch 0][Batch 10099], Speed: 5.964 samples/sec, RPN_Conf=0.063,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.332,RCNN_SmoothL1=0.323,RPNAcc=0.974,RPNL1Loss=0.382,RCNNAcc=0.911,RCNNL1Loss=1.259 +[Epoch 0][Batch 10199], Speed: 5.875 samples/sec, RPN_Conf=0.063,RPN_SmoothL1=0.065,RCNN_CrossEntropy=0.331,RCNN_SmoothL1=0.323,RPNAcc=0.975,RPNL1Loss=0.382,RCNNAcc=0.911,RCNNL1Loss=1.257 +[Epoch 0][Batch 10299], Speed: 5.676 samples/sec, RPN_Conf=0.063,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.330,RCNN_SmoothL1=0.323,RPNAcc=0.975,RPNL1Loss=0.381,RCNNAcc=0.911,RCNNL1Loss=1.254 +[Epoch 0][Batch 10399], Speed: 5.332 samples/sec, RPN_Conf=0.063,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.330,RCNN_SmoothL1=0.323,RPNAcc=0.975,RPNL1Loss=0.381,RCNNAcc=0.911,RCNNL1Loss=1.251 +[Epoch 0][Batch 10499], Speed: 5.970 samples/sec, RPN_Conf=0.063,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.329,RCNN_SmoothL1=0.322,RPNAcc=0.975,RPNL1Loss=0.380,RCNNAcc=0.912,RCNNL1Loss=1.249 +[Epoch 0][Batch 10599], Speed: 6.476 samples/sec, RPN_Conf=0.062,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.328,RCNN_SmoothL1=0.322,RPNAcc=0.975,RPNL1Loss=0.379,RCNNAcc=0.912,RCNNL1Loss=1.246 +[Epoch 0][Batch 10699], Speed: 6.138 samples/sec, RPN_Conf=0.062,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.328,RCNN_SmoothL1=0.322,RPNAcc=0.975,RPNL1Loss=0.379,RCNNAcc=0.912,RCNNL1Loss=1.244 +[Epoch 0][Batch 10799], Speed: 5.751 samples/sec, RPN_Conf=0.062,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.327,RCNN_SmoothL1=0.322,RPNAcc=0.975,RPNL1Loss=0.378,RCNNAcc=0.912,RCNNL1Loss=1.241 +[Epoch 0][Batch 10899], Speed: 6.171 samples/sec, RPN_Conf=0.062,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.326,RCNN_SmoothL1=0.322,RPNAcc=0.975,RPNL1Loss=0.377,RCNNAcc=0.912,RCNNL1Loss=1.239 +[Epoch 0][Batch 10999], Speed: 6.445 samples/sec, RPN_Conf=0.062,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.326,RCNN_SmoothL1=0.321,RPNAcc=0.975,RPNL1Loss=0.377,RCNNAcc=0.912,RCNNL1Loss=1.236 +[Epoch 0][Batch 11099], Speed: 5.785 samples/sec, RPN_Conf=0.061,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.325,RCNN_SmoothL1=0.321,RPNAcc=0.975,RPNL1Loss=0.376,RCNNAcc=0.912,RCNNL1Loss=1.234 +[Epoch 0][Batch 11199], Speed: 6.305 samples/sec, RPN_Conf=0.061,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.324,RCNN_SmoothL1=0.321,RPNAcc=0.975,RPNL1Loss=0.376,RCNNAcc=0.912,RCNNL1Loss=1.232 +[Epoch 0][Batch 11299], Speed: 6.469 samples/sec, RPN_Conf=0.061,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.323,RCNN_SmoothL1=0.321,RPNAcc=0.975,RPNL1Loss=0.375,RCNNAcc=0.912,RCNNL1Loss=1.229 +[Epoch 0][Batch 11399], Speed: 5.941 samples/sec, RPN_Conf=0.061,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.323,RCNN_SmoothL1=0.320,RPNAcc=0.976,RPNL1Loss=0.375,RCNNAcc=0.912,RCNNL1Loss=1.227 +[Epoch 0][Batch 11499], Speed: 5.443 samples/sec, RPN_Conf=0.061,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.322,RCNN_SmoothL1=0.320,RPNAcc=0.976,RPNL1Loss=0.374,RCNNAcc=0.912,RCNNL1Loss=1.224 +[Epoch 0][Batch 11599], Speed: 6.520 samples/sec, RPN_Conf=0.061,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.321,RCNN_SmoothL1=0.320,RPNAcc=0.976,RPNL1Loss=0.374,RCNNAcc=0.912,RCNNL1Loss=1.222 +[Epoch 0][Batch 11699], Speed: 5.897 samples/sec, RPN_Conf=0.061,RPN_SmoothL1=0.064,RCNN_CrossEntropy=0.321,RCNN_SmoothL1=0.320,RPNAcc=0.976,RPNL1Loss=0.373,RCNNAcc=0.913,RCNNL1Loss=1.220 +[Epoch 0][Batch 11799], Speed: 5.776 samples/sec, RPN_Conf=0.060,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.320,RCNN_SmoothL1=0.320,RPNAcc=0.976,RPNL1Loss=0.373,RCNNAcc=0.913,RCNNL1Loss=1.218 +[Epoch 0][Batch 11899], Speed: 6.142 samples/sec, RPN_Conf=0.060,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.320,RCNN_SmoothL1=0.319,RPNAcc=0.976,RPNL1Loss=0.372,RCNNAcc=0.913,RCNNL1Loss=1.215 +[Epoch 0][Batch 11999], Speed: 5.763 samples/sec, RPN_Conf=0.060,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.319,RCNN_SmoothL1=0.319,RPNAcc=0.976,RPNL1Loss=0.372,RCNNAcc=0.913,RCNNL1Loss=1.213 +[Epoch 0][Batch 12099], Speed: 6.162 samples/sec, RPN_Conf=0.060,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.318,RCNN_SmoothL1=0.319,RPNAcc=0.976,RPNL1Loss=0.371,RCNNAcc=0.913,RCNNL1Loss=1.211 +[Epoch 0][Batch 12199], Speed: 6.193 samples/sec, RPN_Conf=0.060,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.318,RCNN_SmoothL1=0.319,RPNAcc=0.976,RPNL1Loss=0.371,RCNNAcc=0.913,RCNNL1Loss=1.209 +[Epoch 0][Batch 12299], Speed: 5.964 samples/sec, RPN_Conf=0.060,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.317,RCNN_SmoothL1=0.318,RPNAcc=0.976,RPNL1Loss=0.370,RCNNAcc=0.913,RCNNL1Loss=1.207 +[Epoch 0][Batch 12399], Speed: 6.297 samples/sec, RPN_Conf=0.060,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.317,RCNN_SmoothL1=0.318,RPNAcc=0.976,RPNL1Loss=0.370,RCNNAcc=0.913,RCNNL1Loss=1.204 +[Epoch 0][Batch 12499], Speed: 6.425 samples/sec, RPN_Conf=0.059,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.316,RCNN_SmoothL1=0.318,RPNAcc=0.976,RPNL1Loss=0.369,RCNNAcc=0.913,RCNNL1Loss=1.202 +[Epoch 0][Batch 12599], Speed: 5.451 samples/sec, RPN_Conf=0.059,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.316,RCNN_SmoothL1=0.318,RPNAcc=0.976,RPNL1Loss=0.369,RCNNAcc=0.913,RCNNL1Loss=1.200 +[Epoch 0][Batch 12699], Speed: 6.014 samples/sec, RPN_Conf=0.059,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.315,RCNN_SmoothL1=0.318,RPNAcc=0.976,RPNL1Loss=0.368,RCNNAcc=0.913,RCNNL1Loss=1.198 +[Epoch 0][Batch 12799], Speed: 6.088 samples/sec, RPN_Conf=0.059,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.315,RCNN_SmoothL1=0.317,RPNAcc=0.977,RPNL1Loss=0.368,RCNNAcc=0.913,RCNNL1Loss=1.196 +[Epoch 0][Batch 12899], Speed: 5.904 samples/sec, RPN_Conf=0.059,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.314,RCNN_SmoothL1=0.317,RPNAcc=0.977,RPNL1Loss=0.367,RCNNAcc=0.913,RCNNL1Loss=1.194 +[Epoch 0][Batch 12999], Speed: 6.030 samples/sec, RPN_Conf=0.059,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.313,RCNN_SmoothL1=0.317,RPNAcc=0.977,RPNL1Loss=0.367,RCNNAcc=0.913,RCNNL1Loss=1.192 +[Epoch 0][Batch 13099], Speed: 5.832 samples/sec, RPN_Conf=0.059,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.313,RCNN_SmoothL1=0.317,RPNAcc=0.977,RPNL1Loss=0.366,RCNNAcc=0.914,RCNNL1Loss=1.190 +[Epoch 0][Batch 13199], Speed: 6.095 samples/sec, RPN_Conf=0.058,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.312,RCNN_SmoothL1=0.317,RPNAcc=0.977,RPNL1Loss=0.366,RCNNAcc=0.914,RCNNL1Loss=1.188 +[Epoch 0][Batch 13299], Speed: 6.173 samples/sec, RPN_Conf=0.058,RPN_SmoothL1=0.063,RCNN_CrossEntropy=0.312,RCNN_SmoothL1=0.316,RPNAcc=0.977,RPNL1Loss=0.365,RCNNAcc=0.914,RCNNL1Loss=1.186 +[Epoch 0][Batch 13399], Speed: 6.029 samples/sec, RPN_Conf=0.058,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.311,RCNN_SmoothL1=0.316,RPNAcc=0.977,RPNL1Loss=0.365,RCNNAcc=0.914,RCNNL1Loss=1.184 +[Epoch 0][Batch 13499], Speed: 6.123 samples/sec, RPN_Conf=0.058,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.311,RCNN_SmoothL1=0.316,RPNAcc=0.977,RPNL1Loss=0.364,RCNNAcc=0.914,RCNNL1Loss=1.182 +[Epoch 0][Batch 13599], Speed: 5.630 samples/sec, RPN_Conf=0.058,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.310,RCNN_SmoothL1=0.316,RPNAcc=0.977,RPNL1Loss=0.364,RCNNAcc=0.914,RCNNL1Loss=1.181 +[Epoch 0][Batch 13699], Speed: 6.285 samples/sec, RPN_Conf=0.058,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.309,RCNN_SmoothL1=0.315,RPNAcc=0.977,RPNL1Loss=0.364,RCNNAcc=0.914,RCNNL1Loss=1.179 +[Epoch 0][Batch 13799], Speed: 6.265 samples/sec, RPN_Conf=0.058,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.309,RCNN_SmoothL1=0.315,RPNAcc=0.977,RPNL1Loss=0.363,RCNNAcc=0.914,RCNNL1Loss=1.177 +[Epoch 0][Batch 13899], Speed: 6.084 samples/sec, RPN_Conf=0.058,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.309,RCNN_SmoothL1=0.315,RPNAcc=0.977,RPNL1Loss=0.363,RCNNAcc=0.914,RCNNL1Loss=1.175 +[Epoch 0][Batch 13999], Speed: 5.567 samples/sec, RPN_Conf=0.057,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.308,RCNN_SmoothL1=0.315,RPNAcc=0.977,RPNL1Loss=0.362,RCNNAcc=0.914,RCNNL1Loss=1.173 +[Epoch 0][Batch 14099], Speed: 6.259 samples/sec, RPN_Conf=0.057,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.307,RCNN_SmoothL1=0.314,RPNAcc=0.977,RPNL1Loss=0.362,RCNNAcc=0.914,RCNNL1Loss=1.172 +[Epoch 0][Batch 14199], Speed: 5.885 samples/sec, RPN_Conf=0.057,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.307,RCNN_SmoothL1=0.314,RPNAcc=0.977,RPNL1Loss=0.361,RCNNAcc=0.914,RCNNL1Loss=1.170 +[Epoch 0][Batch 14299], Speed: 6.000 samples/sec, RPN_Conf=0.057,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.307,RCNN_SmoothL1=0.314,RPNAcc=0.977,RPNL1Loss=0.361,RCNNAcc=0.914,RCNNL1Loss=1.168 +[Epoch 0][Batch 14399], Speed: 5.810 samples/sec, RPN_Conf=0.057,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.306,RCNN_SmoothL1=0.314,RPNAcc=0.977,RPNL1Loss=0.360,RCNNAcc=0.915,RCNNL1Loss=1.167 +[Epoch 0][Batch 14499], Speed: 5.786 samples/sec, RPN_Conf=0.057,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.306,RCNN_SmoothL1=0.314,RPNAcc=0.977,RPNL1Loss=0.360,RCNNAcc=0.915,RCNNL1Loss=1.165 +[Epoch 0][Batch 14599], Speed: 5.944 samples/sec, RPN_Conf=0.057,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.305,RCNN_SmoothL1=0.314,RPNAcc=0.978,RPNL1Loss=0.360,RCNNAcc=0.915,RCNNL1Loss=1.163 +[Epoch 0] Training cost: 19537.977, RPN_Conf=0.057,RPN_SmoothL1=0.062,RCNN_CrossEntropy=0.305,RCNN_SmoothL1=0.314 +[Epoch 0] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.277 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.503 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.281 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.179 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.312 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.333 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.246 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.427 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.463 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.314 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.498 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.544 +person=45.4 +bicycle=21.9 +car=34.4 +motorcycle=30.8 +airplane=45.8 +bus=50.0 +train=46.0 +truck=18.4 +boat=17.8 +traffic light=23.7 +fire hydrant=55.2 +stop sign=47.8 +parking meter=32.4 +bench=13.5 +bird=29.0 +cat=48.7 +dog=46.0 +horse=33.9 +sheep=36.5 +cow=39.7 +elephant=47.3 +bear=54.3 +zebra=52.3 +giraffe=52.5 +backpack=7.9 +umbrella=24.7 +handbag=6.2 +tie=18.6 +suitcase=21.4 +frisbee=54.3 +skis=9.5 +snowboard=12.6 +sports ball=35.5 +kite=32.1 +baseball bat=18.9 +baseball glove=27.3 +skateboard=32.3 +surfboard=25.8 +tennis racket=36.5 +bottle=30.6 +wine glass=25.2 +cup=33.7 +fork=14.0 +knife=8.2 +spoon=8.7 +bowl=28.6 +banana=13.6 +apple=11.7 +sandwich=19.2 +orange=23.0 +broccoli=16.3 +carrot=12.2 +hot dog=16.6 +pizza=40.0 +donut=34.8 +cake=19.3 +chair=17.2 +couch=27.8 +potted plant=16.0 +bed=25.2 +dining table=12.4 +toilet=39.2 +tv=44.4 +laptop=42.7 +mouse=44.4 +remote=15.7 +keyboard=28.5 +cell phone=21.4 +microwave=43.2 +oven=18.1 +toaster=0.0 +sink=24.1 +refrigerator=32.7 +book=9.9 +clock=45.7 +vase=25.0 +scissors=9.5 +teddy bear=26.3 +hair drier=0.0 +toothbrush=3.3 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=27.7 +[Epoch 0] mAP 27.7 higher than current best [0] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 0] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0000_27.7000.params +[Epoch 1][Batch 99], Speed: 6.262 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.054,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.287,RPNAcc=0.978,RPNL1Loss=0.359,RCNNAcc=0.915,RCNNL1Loss=1.160 +[Epoch 1][Batch 199], Speed: 6.668 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.285,RPNAcc=0.978,RPNL1Loss=0.359,RCNNAcc=0.915,RCNNL1Loss=1.158 +[Epoch 1][Batch 299], Speed: 6.091 samples/sec, RPN_Conf=0.036,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.232,RCNN_SmoothL1=0.290,RPNAcc=0.978,RPNL1Loss=0.358,RCNNAcc=0.915,RCNNL1Loss=1.156 +[Epoch 1][Batch 399], Speed: 6.013 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.232,RCNN_SmoothL1=0.288,RPNAcc=0.978,RPNL1Loss=0.358,RCNNAcc=0.915,RCNNL1Loss=1.155 +[Epoch 1][Batch 499], Speed: 7.209 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.231,RCNN_SmoothL1=0.286,RPNAcc=0.978,RPNL1Loss=0.357,RCNNAcc=0.915,RCNNL1Loss=1.153 +[Epoch 1][Batch 599], Speed: 6.275 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.285,RPNAcc=0.978,RPNL1Loss=0.357,RCNNAcc=0.915,RCNNL1Loss=1.151 +[Epoch 1][Batch 699], Speed: 5.920 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.231,RCNN_SmoothL1=0.285,RPNAcc=0.978,RPNL1Loss=0.356,RCNNAcc=0.915,RCNNL1Loss=1.149 +[Epoch 1][Batch 799], Speed: 6.291 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.978,RPNL1Loss=0.356,RCNNAcc=0.915,RCNNL1Loss=1.148 +[Epoch 1][Batch 899], Speed: 6.667 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.978,RPNL1Loss=0.356,RCNNAcc=0.915,RCNNL1Loss=1.146 +[Epoch 1][Batch 999], Speed: 5.809 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.978,RPNL1Loss=0.355,RCNNAcc=0.915,RCNNL1Loss=1.144 +[Epoch 1][Batch 1099], Speed: 6.113 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.978,RPNL1Loss=0.355,RCNNAcc=0.915,RCNNL1Loss=1.143 +[Epoch 1][Batch 1199], Speed: 5.860 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.231,RCNN_SmoothL1=0.284,RPNAcc=0.978,RPNL1Loss=0.354,RCNNAcc=0.916,RCNNL1Loss=1.141 +[Epoch 1][Batch 1299], Speed: 5.431 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.232,RCNN_SmoothL1=0.285,RPNAcc=0.978,RPNL1Loss=0.354,RCNNAcc=0.916,RCNNL1Loss=1.140 +[Epoch 1][Batch 1399], Speed: 5.871 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.232,RCNN_SmoothL1=0.285,RPNAcc=0.978,RPNL1Loss=0.354,RCNNAcc=0.916,RCNNL1Loss=1.138 +[Epoch 1][Batch 1499], Speed: 6.232 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.232,RCNN_SmoothL1=0.285,RPNAcc=0.978,RPNL1Loss=0.353,RCNNAcc=0.916,RCNNL1Loss=1.137 +[Epoch 1][Batch 1599], Speed: 5.786 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.233,RCNN_SmoothL1=0.286,RPNAcc=0.978,RPNL1Loss=0.353,RCNNAcc=0.916,RCNNL1Loss=1.136 +[Epoch 1][Batch 1699], Speed: 5.332 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.231,RCNN_SmoothL1=0.285,RPNAcc=0.978,RPNL1Loss=0.353,RCNNAcc=0.916,RCNNL1Loss=1.134 +[Epoch 1][Batch 1799], Speed: 5.697 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.231,RCNN_SmoothL1=0.284,RPNAcc=0.978,RPNL1Loss=0.352,RCNNAcc=0.916,RCNNL1Loss=1.132 +[Epoch 1][Batch 1899], Speed: 6.333 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.352,RCNNAcc=0.916,RCNNL1Loss=1.131 +[Epoch 1][Batch 1999], Speed: 5.853 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.351,RCNNAcc=0.916,RCNNL1Loss=1.129 +[Epoch 1][Batch 2099], Speed: 6.060 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.351,RCNNAcc=0.916,RCNNL1Loss=1.128 +[Epoch 1][Batch 2199], Speed: 5.915 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.351,RCNNAcc=0.916,RCNNL1Loss=1.127 +[Epoch 1][Batch 2299], Speed: 5.996 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.350,RCNNAcc=0.916,RCNNL1Loss=1.125 +[Epoch 1][Batch 2399], Speed: 5.891 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.350,RCNNAcc=0.916,RCNNL1Loss=1.124 +[Epoch 1][Batch 2499], Speed: 5.796 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.350,RCNNAcc=0.916,RCNNL1Loss=1.122 +[Epoch 1][Batch 2599], Speed: 6.065 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.349,RCNNAcc=0.916,RCNNL1Loss=1.121 +[Epoch 1][Batch 2699], Speed: 5.799 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.284,RPNAcc=0.979,RPNL1Loss=0.349,RCNNAcc=0.916,RCNNL1Loss=1.120 +[Epoch 1][Batch 2799], Speed: 6.286 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.349,RCNNAcc=0.916,RCNNL1Loss=1.118 +[Epoch 1][Batch 2899], Speed: 6.097 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.348,RCNNAcc=0.917,RCNNL1Loss=1.117 +[Epoch 1][Batch 2999], Speed: 6.153 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.348,RCNNAcc=0.917,RCNNL1Loss=1.116 +[Epoch 1][Batch 3099], Speed: 5.883 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.348,RCNNAcc=0.917,RCNNL1Loss=1.114 +[Epoch 1][Batch 3199], Speed: 5.445 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.347,RCNNAcc=0.917,RCNNL1Loss=1.113 +[Epoch 1][Batch 3299], Speed: 6.215 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.347,RCNNAcc=0.917,RCNNL1Loss=1.112 +[Epoch 1][Batch 3399], Speed: 6.113 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.230,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.347,RCNNAcc=0.917,RCNNL1Loss=1.110 +[Epoch 1][Batch 3499], Speed: 5.599 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.346,RCNNAcc=0.917,RCNNL1Loss=1.109 +[Epoch 1][Batch 3599], Speed: 6.077 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.346,RCNNAcc=0.917,RCNNL1Loss=1.108 +[Epoch 1][Batch 3699], Speed: 5.695 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.346,RCNNAcc=0.917,RCNNL1Loss=1.107 +[Epoch 1][Batch 3799], Speed: 5.923 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.346,RCNNAcc=0.917,RCNNL1Loss=1.105 +[Epoch 1][Batch 3899], Speed: 5.983 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.345,RCNNAcc=0.917,RCNNL1Loss=1.104 +[Epoch 1][Batch 3999], Speed: 5.995 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.345,RCNNAcc=0.917,RCNNL1Loss=1.103 +[Epoch 1][Batch 4099], Speed: 6.171 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.345,RCNNAcc=0.917,RCNNL1Loss=1.102 +[Epoch 1][Batch 4199], Speed: 6.030 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.344,RCNNAcc=0.917,RCNNL1Loss=1.101 +[Epoch 1][Batch 4299], Speed: 5.607 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.344,RCNNAcc=0.917,RCNNL1Loss=1.100 +[Epoch 1][Batch 4399], Speed: 5.447 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.979,RPNL1Loss=0.344,RCNNAcc=0.917,RCNNL1Loss=1.098 +[Epoch 1][Batch 4499], Speed: 5.559 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.980,RPNL1Loss=0.343,RCNNAcc=0.917,RCNNL1Loss=1.097 +[Epoch 1][Batch 4599], Speed: 5.536 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.980,RPNL1Loss=0.343,RCNNAcc=0.917,RCNNL1Loss=1.096 +[Epoch 1][Batch 4699], Speed: 5.992 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.980,RPNL1Loss=0.343,RCNNAcc=0.917,RCNNL1Loss=1.095 +[Epoch 1][Batch 4799], Speed: 5.948 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.980,RPNL1Loss=0.342,RCNNAcc=0.917,RCNNL1Loss=1.094 +[Epoch 1][Batch 4899], Speed: 5.860 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.980,RPNL1Loss=0.342,RCNNAcc=0.917,RCNNL1Loss=1.092 +[Epoch 1][Batch 4999], Speed: 6.126 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.283,RPNAcc=0.980,RPNL1Loss=0.342,RCNNAcc=0.918,RCNNL1Loss=1.091 +[Epoch 1][Batch 5099], Speed: 5.976 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.342,RCNNAcc=0.918,RCNNL1Loss=1.090 +[Epoch 1][Batch 5199], Speed: 5.862 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.341,RCNNAcc=0.918,RCNNL1Loss=1.089 +[Epoch 1][Batch 5299], Speed: 6.545 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.341,RCNNAcc=0.918,RCNNL1Loss=1.088 +[Epoch 1][Batch 5399], Speed: 5.940 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.341,RCNNAcc=0.918,RCNNL1Loss=1.087 +[Epoch 1][Batch 5499], Speed: 5.515 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.341,RCNNAcc=0.918,RCNNL1Loss=1.086 +[Epoch 1][Batch 5599], Speed: 5.913 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.340,RCNNAcc=0.918,RCNNL1Loss=1.085 +[Epoch 1][Batch 5699], Speed: 5.948 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.340,RCNNAcc=0.918,RCNNL1Loss=1.084 +[Epoch 1][Batch 5799], Speed: 6.538 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.340,RCNNAcc=0.918,RCNNL1Loss=1.083 +[Epoch 1][Batch 5899], Speed: 5.598 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.340,RCNNAcc=0.918,RCNNL1Loss=1.082 +[Epoch 1][Batch 5999], Speed: 5.797 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.339,RCNNAcc=0.918,RCNNL1Loss=1.081 +[Epoch 1][Batch 6099], Speed: 6.013 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.339,RCNNAcc=0.918,RCNNL1Loss=1.080 +[Epoch 1][Batch 6199], Speed: 6.060 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.339,RCNNAcc=0.918,RCNNL1Loss=1.079 +[Epoch 1][Batch 6299], Speed: 5.491 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.339,RCNNAcc=0.918,RCNNL1Loss=1.077 +[Epoch 1][Batch 6399], Speed: 6.094 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.229,RCNN_SmoothL1=0.282,RPNAcc=0.980,RPNL1Loss=0.338,RCNNAcc=0.918,RCNNL1Loss=1.076 +[Epoch 1][Batch 6499], Speed: 6.188 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.281,RPNAcc=0.980,RPNL1Loss=0.338,RCNNAcc=0.918,RCNNL1Loss=1.075 +[Epoch 1][Batch 6599], Speed: 6.289 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.281,RPNAcc=0.980,RPNL1Loss=0.338,RCNNAcc=0.918,RCNNL1Loss=1.074 +[Epoch 1][Batch 6699], Speed: 6.392 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.281,RPNAcc=0.980,RPNL1Loss=0.338,RCNNAcc=0.918,RCNNL1Loss=1.073 +[Epoch 1][Batch 6799], Speed: 5.546 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.281,RPNAcc=0.980,RPNL1Loss=0.337,RCNNAcc=0.918,RCNNL1Loss=1.072 +[Epoch 1][Batch 6899], Speed: 5.429 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.281,RPNAcc=0.980,RPNL1Loss=0.337,RCNNAcc=0.918,RCNNL1Loss=1.071 +[Epoch 1][Batch 6999], Speed: 6.045 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.281,RPNAcc=0.980,RPNL1Loss=0.337,RCNNAcc=0.918,RCNNL1Loss=1.070 +[Epoch 1][Batch 7099], Speed: 5.700 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.281,RPNAcc=0.980,RPNL1Loss=0.337,RCNNAcc=0.918,RCNNL1Loss=1.069 +[Epoch 1][Batch 7199], Speed: 5.945 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.228,RCNN_SmoothL1=0.281,RPNAcc=0.980,RPNL1Loss=0.336,RCNNAcc=0.918,RCNNL1Loss=1.068 +[Epoch 1][Batch 7299], Speed: 6.080 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.980,RPNL1Loss=0.336,RCNNAcc=0.919,RCNNL1Loss=1.067 +[Epoch 1][Batch 7399], Speed: 5.733 samples/sec, RPN_Conf=0.038,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.980,RPNL1Loss=0.336,RCNNAcc=0.919,RCNNL1Loss=1.066 +[Epoch 1][Batch 7499], Speed: 6.327 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.980,RPNL1Loss=0.336,RCNNAcc=0.919,RCNNL1Loss=1.065 +[Epoch 1][Batch 7599], Speed: 6.012 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.980,RPNL1Loss=0.335,RCNNAcc=0.919,RCNNL1Loss=1.064 +[Epoch 1][Batch 7699], Speed: 6.364 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.980,RPNL1Loss=0.335,RCNNAcc=0.919,RCNNL1Loss=1.063 +[Epoch 1][Batch 7799], Speed: 5.893 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.980,RPNL1Loss=0.335,RCNNAcc=0.919,RCNNL1Loss=1.062 +[Epoch 1][Batch 7899], Speed: 5.922 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.980,RPNL1Loss=0.335,RCNNAcc=0.919,RCNNL1Loss=1.061 +[Epoch 1][Batch 7999], Speed: 6.191 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.981,RPNL1Loss=0.334,RCNNAcc=0.919,RCNNL1Loss=1.060 +[Epoch 1][Batch 8099], Speed: 5.993 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.981,RPNL1Loss=0.334,RCNNAcc=0.919,RCNNL1Loss=1.059 +[Epoch 1][Batch 8199], Speed: 6.000 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.981,RPNL1Loss=0.334,RCNNAcc=0.919,RCNNL1Loss=1.059 +[Epoch 1][Batch 8299], Speed: 5.984 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.053,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.981,RPNL1Loss=0.334,RCNNAcc=0.919,RCNNL1Loss=1.058 +[Epoch 1][Batch 8399], Speed: 6.578 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.981,RPNL1Loss=0.334,RCNNAcc=0.919,RCNNL1Loss=1.057 +[Epoch 1][Batch 8499], Speed: 5.944 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.280,RPNAcc=0.981,RPNL1Loss=0.333,RCNNAcc=0.919,RCNNL1Loss=1.056 +[Epoch 1][Batch 8599], Speed: 5.971 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.333,RCNNAcc=0.919,RCNNL1Loss=1.055 +[Epoch 1][Batch 8699], Speed: 5.992 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.333,RCNNAcc=0.919,RCNNL1Loss=1.054 +[Epoch 1][Batch 8799], Speed: 6.159 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.333,RCNNAcc=0.919,RCNNL1Loss=1.053 +[Epoch 1][Batch 8899], Speed: 5.988 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.332,RCNNAcc=0.919,RCNNL1Loss=1.052 +[Epoch 1][Batch 8999], Speed: 5.681 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.332,RCNNAcc=0.919,RCNNL1Loss=1.051 +[Epoch 1][Batch 9099], Speed: 5.864 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.332,RCNNAcc=0.919,RCNNL1Loss=1.050 +[Epoch 1][Batch 9199], Speed: 5.531 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.227,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.332,RCNNAcc=0.919,RCNNL1Loss=1.050 +[Epoch 1][Batch 9299], Speed: 6.269 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.332,RCNNAcc=0.919,RCNNL1Loss=1.049 +[Epoch 1][Batch 9399], Speed: 5.708 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.331,RCNNAcc=0.919,RCNNL1Loss=1.048 +[Epoch 1][Batch 9499], Speed: 6.144 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.331,RCNNAcc=0.919,RCNNL1Loss=1.047 +[Epoch 1][Batch 9599], Speed: 6.091 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.331,RCNNAcc=0.919,RCNNL1Loss=1.046 +[Epoch 1][Batch 9699], Speed: 6.145 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.331,RCNNAcc=0.919,RCNNL1Loss=1.046 +[Epoch 1][Batch 9799], Speed: 5.710 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.331,RCNNAcc=0.919,RCNNL1Loss=1.045 +[Epoch 1][Batch 9899], Speed: 5.893 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.330,RCNNAcc=0.919,RCNNL1Loss=1.044 +[Epoch 1][Batch 9999], Speed: 5.704 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.330,RCNNAcc=0.920,RCNNL1Loss=1.043 +[Epoch 1][Batch 10099], Speed: 6.765 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.330,RCNNAcc=0.920,RCNNL1Loss=1.043 +[Epoch 1][Batch 10199], Speed: 6.162 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.330,RCNNAcc=0.920,RCNNL1Loss=1.042 +[Epoch 1][Batch 10299], Speed: 5.875 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.329,RCNNAcc=0.920,RCNNL1Loss=1.041 +[Epoch 1][Batch 10399], Speed: 5.666 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.279,RPNAcc=0.981,RPNL1Loss=0.329,RCNNAcc=0.920,RCNNL1Loss=1.040 +[Epoch 1][Batch 10499], Speed: 5.778 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.329,RCNNAcc=0.920,RCNNL1Loss=1.039 +[Epoch 1][Batch 10599], Speed: 6.316 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.329,RCNNAcc=0.920,RCNNL1Loss=1.039 +[Epoch 1][Batch 10699], Speed: 5.534 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.329,RCNNAcc=0.920,RCNNL1Loss=1.038 +[Epoch 1][Batch 10799], Speed: 5.903 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.328,RCNNAcc=0.920,RCNNL1Loss=1.037 +[Epoch 1][Batch 10899], Speed: 6.078 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.328,RCNNAcc=0.920,RCNNL1Loss=1.036 +[Epoch 1][Batch 10999], Speed: 5.313 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.328,RCNNAcc=0.920,RCNNL1Loss=1.035 +[Epoch 1][Batch 11099], Speed: 6.141 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.328,RCNNAcc=0.920,RCNNL1Loss=1.035 +[Epoch 1][Batch 11199], Speed: 5.789 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.328,RCNNAcc=0.920,RCNNL1Loss=1.034 +[Epoch 1][Batch 11299], Speed: 5.588 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.327,RCNNAcc=0.920,RCNNL1Loss=1.033 +[Epoch 1][Batch 11399], Speed: 5.906 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.226,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.327,RCNNAcc=0.920,RCNNL1Loss=1.032 +[Epoch 1][Batch 11499], Speed: 6.043 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.327,RCNNAcc=0.920,RCNNL1Loss=1.032 +[Epoch 1][Batch 11599], Speed: 5.985 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.327,RCNNAcc=0.920,RCNNL1Loss=1.031 +[Epoch 1][Batch 11699], Speed: 5.480 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.327,RCNNAcc=0.920,RCNNL1Loss=1.030 +[Epoch 1][Batch 11799], Speed: 6.300 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.278,RPNAcc=0.981,RPNL1Loss=0.326,RCNNAcc=0.920,RCNNL1Loss=1.029 +[Epoch 1][Batch 11899], Speed: 5.474 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.981,RPNL1Loss=0.326,RCNNAcc=0.920,RCNNL1Loss=1.028 +[Epoch 1][Batch 11999], Speed: 6.248 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.981,RPNL1Loss=0.326,RCNNAcc=0.920,RCNNL1Loss=1.028 +[Epoch 1][Batch 12099], Speed: 6.034 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.981,RPNL1Loss=0.326,RCNNAcc=0.920,RCNNL1Loss=1.027 +[Epoch 1][Batch 12199], Speed: 6.611 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.981,RPNL1Loss=0.326,RCNNAcc=0.920,RCNNL1Loss=1.026 +[Epoch 1][Batch 12299], Speed: 6.124 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.981,RPNL1Loss=0.326,RCNNAcc=0.920,RCNNL1Loss=1.026 +[Epoch 1][Batch 12399], Speed: 5.934 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.981,RPNL1Loss=0.325,RCNNAcc=0.920,RCNNL1Loss=1.025 +[Epoch 1][Batch 12499], Speed: 6.096 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.981,RPNL1Loss=0.325,RCNNAcc=0.920,RCNNL1Loss=1.024 +[Epoch 1][Batch 12599], Speed: 6.240 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.981,RPNL1Loss=0.325,RCNNAcc=0.920,RCNNL1Loss=1.023 +[Epoch 1][Batch 12699], Speed: 6.134 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.982,RPNL1Loss=0.325,RCNNAcc=0.920,RCNNL1Loss=1.023 +[Epoch 1][Batch 12799], Speed: 6.255 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.982,RPNL1Loss=0.325,RCNNAcc=0.920,RCNNL1Loss=1.022 +[Epoch 1][Batch 12899], Speed: 5.906 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.982,RPNL1Loss=0.324,RCNNAcc=0.920,RCNNL1Loss=1.021 +[Epoch 1][Batch 12999], Speed: 5.609 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.982,RPNL1Loss=0.324,RCNNAcc=0.920,RCNNL1Loss=1.020 +[Epoch 1][Batch 13099], Speed: 6.065 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.225,RCNN_SmoothL1=0.277,RPNAcc=0.982,RPNL1Loss=0.324,RCNNAcc=0.921,RCNNL1Loss=1.019 +[Epoch 1][Batch 13199], Speed: 5.601 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.277,RPNAcc=0.982,RPNL1Loss=0.324,RCNNAcc=0.921,RCNNL1Loss=1.019 +[Epoch 1][Batch 13299], Speed: 5.988 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.324,RCNNAcc=0.921,RCNNL1Loss=1.018 +[Epoch 1][Batch 13399], Speed: 6.140 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.323,RCNNAcc=0.921,RCNNL1Loss=1.017 +[Epoch 1][Batch 13499], Speed: 5.864 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.323,RCNNAcc=0.921,RCNNL1Loss=1.017 +[Epoch 1][Batch 13599], Speed: 6.003 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.323,RCNNAcc=0.921,RCNNL1Loss=1.016 +[Epoch 1][Batch 13699], Speed: 5.589 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.323,RCNNAcc=0.921,RCNNL1Loss=1.015 +[Epoch 1][Batch 13799], Speed: 6.001 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.323,RCNNAcc=0.921,RCNNL1Loss=1.015 +[Epoch 1][Batch 13899], Speed: 6.003 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.323,RCNNAcc=0.921,RCNNL1Loss=1.014 +[Epoch 1][Batch 13999], Speed: 5.800 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.322,RCNNAcc=0.921,RCNNL1Loss=1.013 +[Epoch 1][Batch 14099], Speed: 5.701 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.322,RCNNAcc=0.921,RCNNL1Loss=1.013 +[Epoch 1][Batch 14199], Speed: 5.624 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.322,RCNNAcc=0.921,RCNNL1Loss=1.012 +[Epoch 1][Batch 14299], Speed: 6.163 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.322,RCNNAcc=0.921,RCNNL1Loss=1.012 +[Epoch 1][Batch 14399], Speed: 5.763 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.322,RCNNAcc=0.921,RCNNL1Loss=1.011 +[Epoch 1][Batch 14499], Speed: 5.986 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.322,RCNNAcc=0.921,RCNNL1Loss=1.010 +[Epoch 1][Batch 14599], Speed: 6.067 samples/sec, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276,RPNAcc=0.982,RPNL1Loss=0.321,RCNNAcc=0.921,RCNNL1Loss=1.010 +[Epoch 1] Training cost: 19697.430, RPN_Conf=0.037,RPN_SmoothL1=0.052,RCNN_CrossEntropy=0.224,RCNN_SmoothL1=0.276 +[Epoch 1] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.327 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.550 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.346 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.211 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.371 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.391 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.278 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.460 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.492 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.339 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.533 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.575 +person=48.9 +bicycle=23.6 +car=35.4 +motorcycle=34.0 +airplane=55.6 +bus=58.5 +train=50.6 +truck=26.3 +boat=18.9 +traffic light=24.8 +fire hydrant=56.6 +stop sign=57.6 +parking meter=36.7 +bench=16.6 +bird=28.9 +cat=54.7 +dog=50.2 +horse=45.2 +sheep=41.5 +cow=41.1 +elephant=51.3 +bear=53.0 +zebra=57.4 +giraffe=56.7 +backpack=11.7 +umbrella=29.8 +handbag=10.6 +tie=26.1 +suitcase=30.7 +frisbee=53.2 +skis=12.0 +snowboard=23.0 +sports ball=40.5 +kite=33.3 +baseball bat=20.7 +baseball glove=32.5 +skateboard=39.8 +surfboard=26.5 +tennis racket=38.7 +bottle=35.4 +wine glass=30.0 +cup=38.0 +fork=23.0 +knife=10.5 +spoon=10.7 +bowl=35.2 +banana=15.3 +apple=15.1 +sandwich=23.6 +orange=23.8 +broccoli=21.8 +carrot=17.2 +hot dog=21.5 +pizza=42.0 +donut=40.3 +cake=30.9 +chair=21.3 +couch=32.4 +potted plant=20.9 +bed=29.7 +dining table=16.1 +toilet=51.2 +tv=47.4 +laptop=48.5 +mouse=54.4 +remote=25.9 +keyboard=43.3 +cell phone=31.7 +microwave=46.4 +oven=22.6 +toaster=9.2 +sink=26.7 +refrigerator=44.3 +book=12.4 +clock=47.4 +vase=31.6 +scissors=17.3 +teddy bear=35.2 +hair drier=0.0 +toothbrush=13.9 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=32.7 +[Epoch 1] mAP 32.7 higher than current best [27.7] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 1] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0001_32.7000.params +[Epoch 2][Batch 99], Speed: 6.181 samples/sec, RPN_Conf=0.034,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.196,RCNN_SmoothL1=0.262,RPNAcc=0.982,RPNL1Loss=0.321,RCNNAcc=0.921,RCNNL1Loss=1.009 +[Epoch 2][Batch 199], Speed: 6.100 samples/sec, RPN_Conf=0.034,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.199,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.321,RCNNAcc=0.921,RCNNL1Loss=1.008 +[Epoch 2][Batch 299], Speed: 6.458 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.204,RCNN_SmoothL1=0.264,RPNAcc=0.982,RPNL1Loss=0.321,RCNNAcc=0.921,RCNNL1Loss=1.007 +[Epoch 2][Batch 399], Speed: 5.560 samples/sec, RPN_Conf=0.034,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.204,RCNN_SmoothL1=0.265,RPNAcc=0.982,RPNL1Loss=0.320,RCNNAcc=0.921,RCNNL1Loss=1.006 +[Epoch 2][Batch 499], Speed: 6.366 samples/sec, RPN_Conf=0.034,RPN_SmoothL1=0.050,RCNN_CrossEntropy=0.205,RCNN_SmoothL1=0.265,RPNAcc=0.982,RPNL1Loss=0.320,RCNNAcc=0.921,RCNNL1Loss=1.006 +[Epoch 2][Batch 599], Speed: 6.190 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.050,RCNN_CrossEntropy=0.205,RCNN_SmoothL1=0.266,RPNAcc=0.982,RPNL1Loss=0.320,RCNNAcc=0.921,RCNNL1Loss=1.005 +[Epoch 2][Batch 699], Speed: 6.234 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.050,RCNN_CrossEntropy=0.205,RCNN_SmoothL1=0.264,RPNAcc=0.982,RPNL1Loss=0.320,RCNNAcc=0.921,RCNNL1Loss=1.004 +[Epoch 2][Batch 799], Speed: 6.033 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.204,RCNN_SmoothL1=0.263,RPNAcc=0.982,RPNL1Loss=0.320,RCNNAcc=0.921,RCNNL1Loss=1.003 +[Epoch 2][Batch 899], Speed: 5.643 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.204,RCNN_SmoothL1=0.264,RPNAcc=0.982,RPNL1Loss=0.319,RCNNAcc=0.921,RCNNL1Loss=1.003 +[Epoch 2][Batch 999], Speed: 5.978 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.262,RPNAcc=0.982,RPNL1Loss=0.319,RCNNAcc=0.921,RCNNL1Loss=1.002 +[Epoch 2][Batch 1099], Speed: 6.033 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.262,RPNAcc=0.982,RPNL1Loss=0.319,RCNNAcc=0.921,RCNNL1Loss=1.001 +[Epoch 2][Batch 1199], Speed: 6.276 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.263,RPNAcc=0.982,RPNL1Loss=0.319,RCNNAcc=0.921,RCNNL1Loss=1.001 +[Epoch 2][Batch 1299], Speed: 6.009 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.263,RPNAcc=0.982,RPNL1Loss=0.319,RCNNAcc=0.921,RCNNL1Loss=1.000 +[Epoch 2][Batch 1399], Speed: 5.940 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.262,RPNAcc=0.982,RPNL1Loss=0.319,RCNNAcc=0.921,RCNNL1Loss=0.999 +[Epoch 2][Batch 1499], Speed: 5.448 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.262,RPNAcc=0.982,RPNL1Loss=0.318,RCNNAcc=0.922,RCNNL1Loss=0.999 +[Epoch 2][Batch 1599], Speed: 6.114 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.262,RPNAcc=0.982,RPNL1Loss=0.318,RCNNAcc=0.922,RCNNL1Loss=0.998 +[Epoch 2][Batch 1699], Speed: 5.559 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.262,RPNAcc=0.982,RPNL1Loss=0.318,RCNNAcc=0.922,RCNNL1Loss=0.997 +[Epoch 2][Batch 1799], Speed: 6.394 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.261,RPNAcc=0.982,RPNL1Loss=0.318,RCNNAcc=0.922,RCNNL1Loss=0.997 +[Epoch 2][Batch 1899], Speed: 5.924 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.261,RPNAcc=0.982,RPNL1Loss=0.318,RCNNAcc=0.922,RCNNL1Loss=0.996 +[Epoch 2][Batch 1999], Speed: 6.032 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.261,RPNAcc=0.982,RPNL1Loss=0.317,RCNNAcc=0.922,RCNNL1Loss=0.995 +[Epoch 2][Batch 2099], Speed: 5.715 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.261,RPNAcc=0.982,RPNL1Loss=0.317,RCNNAcc=0.922,RCNNL1Loss=0.995 +[Epoch 2][Batch 2199], Speed: 5.894 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.261,RPNAcc=0.982,RPNL1Loss=0.317,RCNNAcc=0.922,RCNNL1Loss=0.994 +[Epoch 2][Batch 2299], Speed: 6.354 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.317,RCNNAcc=0.922,RCNNL1Loss=0.993 +[Epoch 2][Batch 2399], Speed: 5.820 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.317,RCNNAcc=0.922,RCNNL1Loss=0.993 +[Epoch 2][Batch 2499], Speed: 5.546 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.317,RCNNAcc=0.922,RCNNL1Loss=0.992 +[Epoch 2][Batch 2599], Speed: 6.144 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.316,RCNNAcc=0.922,RCNNL1Loss=0.991 +[Epoch 2][Batch 2699], Speed: 5.958 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.316,RCNNAcc=0.922,RCNNL1Loss=0.991 +[Epoch 2][Batch 2799], Speed: 5.694 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.316,RCNNAcc=0.922,RCNNL1Loss=0.990 +[Epoch 2][Batch 2899], Speed: 5.660 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.316,RCNNAcc=0.922,RCNNL1Loss=0.989 +[Epoch 2][Batch 2999], Speed: 6.153 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.201,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.316,RCNNAcc=0.922,RCNNL1Loss=0.989 +[Epoch 2][Batch 3099], Speed: 5.728 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.316,RCNNAcc=0.922,RCNNL1Loss=0.988 +[Epoch 2][Batch 3199], Speed: 6.158 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.315,RCNNAcc=0.922,RCNNL1Loss=0.988 +[Epoch 2][Batch 3299], Speed: 5.714 samples/sec, RPN_Conf=0.032,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.315,RCNNAcc=0.922,RCNNL1Loss=0.987 +[Epoch 2][Batch 3399], Speed: 6.046 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.315,RCNNAcc=0.922,RCNNL1Loss=0.987 +[Epoch 2][Batch 3499], Speed: 5.868 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.315,RCNNAcc=0.922,RCNNL1Loss=0.986 +[Epoch 2][Batch 3599], Speed: 6.301 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.982,RPNL1Loss=0.315,RCNNAcc=0.922,RCNNL1Loss=0.985 +[Epoch 2][Batch 3699], Speed: 5.745 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.315,RCNNAcc=0.922,RCNNL1Loss=0.985 +[Epoch 2][Batch 3799], Speed: 5.923 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.315,RCNNAcc=0.922,RCNNL1Loss=0.984 +[Epoch 2][Batch 3899], Speed: 5.835 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.314,RCNNAcc=0.922,RCNNL1Loss=0.984 +[Epoch 2][Batch 3999], Speed: 5.776 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.314,RCNNAcc=0.922,RCNNL1Loss=0.983 +[Epoch 2][Batch 4099], Speed: 6.236 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.314,RCNNAcc=0.922,RCNNL1Loss=0.982 +[Epoch 2][Batch 4199], Speed: 5.754 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.314,RCNNAcc=0.922,RCNNL1Loss=0.982 +[Epoch 2][Batch 4299], Speed: 5.849 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.314,RCNNAcc=0.922,RCNNL1Loss=0.981 +[Epoch 2][Batch 4399], Speed: 6.017 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.314,RCNNAcc=0.922,RCNNL1Loss=0.981 +[Epoch 2][Batch 4499], Speed: 5.487 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.314,RCNNAcc=0.922,RCNNL1Loss=0.980 +[Epoch 2][Batch 4599], Speed: 5.547 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.313,RCNNAcc=0.923,RCNNL1Loss=0.980 +[Epoch 2][Batch 4699], Speed: 5.524 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.313,RCNNAcc=0.923,RCNNL1Loss=0.979 +[Epoch 2][Batch 4799], Speed: 5.890 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.313,RCNNAcc=0.923,RCNNL1Loss=0.978 +[Epoch 2][Batch 4899], Speed: 5.755 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.313,RCNNAcc=0.923,RCNNL1Loss=0.978 +[Epoch 2][Batch 4999], Speed: 6.122 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.313,RCNNAcc=0.923,RCNNL1Loss=0.977 +[Epoch 2][Batch 5099], Speed: 6.212 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.313,RCNNAcc=0.923,RCNNL1Loss=0.977 +[Epoch 2][Batch 5199], Speed: 5.800 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.313,RCNNAcc=0.923,RCNNL1Loss=0.976 +[Epoch 2][Batch 5299], Speed: 5.599 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.312,RCNNAcc=0.923,RCNNL1Loss=0.976 +[Epoch 2][Batch 5399], Speed: 5.410 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.312,RCNNAcc=0.923,RCNNL1Loss=0.975 +[Epoch 2][Batch 5499], Speed: 6.126 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.312,RCNNAcc=0.923,RCNNL1Loss=0.975 +[Epoch 2][Batch 5599], Speed: 6.413 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.312,RCNNAcc=0.923,RCNNL1Loss=0.974 +[Epoch 2][Batch 5699], Speed: 5.655 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.312,RCNNAcc=0.923,RCNNL1Loss=0.973 +[Epoch 2][Batch 5799], Speed: 6.184 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.312,RCNNAcc=0.923,RCNNL1Loss=0.973 +[Epoch 2][Batch 5899], Speed: 5.330 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.312,RCNNAcc=0.923,RCNNL1Loss=0.972 +[Epoch 2][Batch 5999], Speed: 6.157 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.311,RCNNAcc=0.923,RCNNL1Loss=0.972 +[Epoch 2][Batch 6099], Speed: 5.669 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.311,RCNNAcc=0.923,RCNNL1Loss=0.971 +[Epoch 2][Batch 6199], Speed: 6.516 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.311,RCNNAcc=0.923,RCNNL1Loss=0.971 +[Epoch 2][Batch 6299], Speed: 5.865 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.311,RCNNAcc=0.923,RCNNL1Loss=0.970 +[Epoch 2][Batch 6399], Speed: 6.592 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.311,RCNNAcc=0.923,RCNNL1Loss=0.970 +[Epoch 2][Batch 6499], Speed: 5.687 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.311,RCNNAcc=0.923,RCNNL1Loss=0.969 +[Epoch 2][Batch 6599], Speed: 5.606 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.311,RCNNAcc=0.923,RCNNL1Loss=0.969 +[Epoch 2][Batch 6699], Speed: 5.806 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.260,RPNAcc=0.983,RPNL1Loss=0.310,RCNNAcc=0.923,RCNNL1Loss=0.968 +[Epoch 2][Batch 6799], Speed: 5.631 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.310,RCNNAcc=0.923,RCNNL1Loss=0.968 +[Epoch 2][Batch 6899], Speed: 6.523 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.310,RCNNAcc=0.923,RCNNL1Loss=0.967 +[Epoch 2][Batch 6999], Speed: 6.044 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.310,RCNNAcc=0.923,RCNNL1Loss=0.967 +[Epoch 2][Batch 7099], Speed: 5.975 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.310,RCNNAcc=0.923,RCNNL1Loss=0.966 +[Epoch 2][Batch 7199], Speed: 5.941 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.310,RCNNAcc=0.923,RCNNL1Loss=0.966 +[Epoch 2][Batch 7299], Speed: 6.018 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.310,RCNNAcc=0.923,RCNNL1Loss=0.965 +[Epoch 2][Batch 7399], Speed: 5.405 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.310,RCNNAcc=0.923,RCNNL1Loss=0.965 +[Epoch 2][Batch 7499], Speed: 5.671 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.309,RCNNAcc=0.923,RCNNL1Loss=0.964 +[Epoch 2][Batch 7599], Speed: 5.615 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.309,RCNNAcc=0.923,RCNNL1Loss=0.964 +[Epoch 2][Batch 7699], Speed: 6.448 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.309,RCNNAcc=0.923,RCNNL1Loss=0.963 +[Epoch 2][Batch 7799], Speed: 5.745 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.309,RCNNAcc=0.923,RCNNL1Loss=0.963 +[Epoch 2][Batch 7899], Speed: 5.651 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.309,RCNNAcc=0.923,RCNNL1Loss=0.962 +[Epoch 2][Batch 7999], Speed: 6.032 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.309,RCNNAcc=0.923,RCNNL1Loss=0.962 +[Epoch 2][Batch 8099], Speed: 6.074 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.309,RCNNAcc=0.923,RCNNL1Loss=0.961 +[Epoch 2][Batch 8199], Speed: 6.178 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.308,RCNNAcc=0.923,RCNNL1Loss=0.961 +[Epoch 2][Batch 8299], Speed: 6.200 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.308,RCNNAcc=0.923,RCNNL1Loss=0.960 +[Epoch 2][Batch 8399], Speed: 5.880 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.308,RCNNAcc=0.924,RCNNL1Loss=0.960 +[Epoch 2][Batch 8499], Speed: 5.842 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.308,RCNNAcc=0.924,RCNNL1Loss=0.959 +[Epoch 2][Batch 8599], Speed: 5.599 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.308,RCNNAcc=0.924,RCNNL1Loss=0.959 +[Epoch 2][Batch 8699], Speed: 6.325 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.259,RPNAcc=0.983,RPNL1Loss=0.308,RCNNAcc=0.924,RCNNL1Loss=0.959 +[Epoch 2][Batch 8799], Speed: 5.975 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.308,RCNNAcc=0.924,RCNNL1Loss=0.958 +[Epoch 2][Batch 8899], Speed: 6.271 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.308,RCNNAcc=0.924,RCNNL1Loss=0.958 +[Epoch 2][Batch 8999], Speed: 6.471 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.307,RCNNAcc=0.924,RCNNL1Loss=0.957 +[Epoch 2][Batch 9099], Speed: 5.827 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.307,RCNNAcc=0.924,RCNNL1Loss=0.957 +[Epoch 2][Batch 9199], Speed: 5.802 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.307,RCNNAcc=0.924,RCNNL1Loss=0.956 +[Epoch 2][Batch 9299], Speed: 6.098 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.307,RCNNAcc=0.924,RCNNL1Loss=0.956 +[Epoch 2][Batch 9399], Speed: 5.897 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.307,RCNNAcc=0.924,RCNNL1Loss=0.955 +[Epoch 2][Batch 9499], Speed: 6.119 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.307,RCNNAcc=0.924,RCNNL1Loss=0.955 +[Epoch 2][Batch 9599], Speed: 6.200 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.307,RCNNAcc=0.924,RCNNL1Loss=0.954 +[Epoch 2][Batch 9699], Speed: 6.356 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.307,RCNNAcc=0.924,RCNNL1Loss=0.954 +[Epoch 2][Batch 9799], Speed: 5.534 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.953 +[Epoch 2][Batch 9899], Speed: 6.277 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.953 +[Epoch 2][Batch 9999], Speed: 5.922 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.953 +[Epoch 2][Batch 10099], Speed: 5.780 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.952 +[Epoch 2][Batch 10199], Speed: 5.847 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.952 +[Epoch 2][Batch 10299], Speed: 6.370 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.951 +[Epoch 2][Batch 10399], Speed: 5.559 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.951 +[Epoch 2][Batch 10499], Speed: 6.540 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.950 +[Epoch 2][Batch 10599], Speed: 5.916 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.306,RCNNAcc=0.924,RCNNL1Loss=0.950 +[Epoch 2][Batch 10699], Speed: 6.223 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.305,RCNNAcc=0.924,RCNNL1Loss=0.949 +[Epoch 2][Batch 10799], Speed: 5.400 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.305,RCNNAcc=0.924,RCNNL1Loss=0.949 +[Epoch 2][Batch 10899], Speed: 5.831 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.305,RCNNAcc=0.924,RCNNL1Loss=0.949 +[Epoch 2][Batch 10999], Speed: 5.627 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.305,RCNNAcc=0.924,RCNNL1Loss=0.948 +[Epoch 2][Batch 11099], Speed: 6.121 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.305,RCNNAcc=0.924,RCNNL1Loss=0.948 +[Epoch 2][Batch 11199], Speed: 5.936 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.305,RCNNAcc=0.924,RCNNL1Loss=0.947 +[Epoch 2][Batch 11299], Speed: 5.932 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.305,RCNNAcc=0.924,RCNNL1Loss=0.947 +[Epoch 2][Batch 11399], Speed: 5.875 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.305,RCNNAcc=0.924,RCNNL1Loss=0.947 +[Epoch 2][Batch 11499], Speed: 5.747 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.946 +[Epoch 2][Batch 11599], Speed: 6.140 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.946 +[Epoch 2][Batch 11699], Speed: 5.857 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.945 +[Epoch 2][Batch 11799], Speed: 6.525 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.983,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.945 +[Epoch 2][Batch 11899], Speed: 6.159 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.945 +[Epoch 2][Batch 11999], Speed: 6.497 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.944 +[Epoch 2][Batch 12099], Speed: 6.015 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.944 +[Epoch 2][Batch 12199], Speed: 6.252 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.943 +[Epoch 2][Batch 12299], Speed: 5.577 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.304,RCNNAcc=0.924,RCNNL1Loss=0.943 +[Epoch 2][Batch 12399], Speed: 5.953 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.924,RCNNL1Loss=0.942 +[Epoch 2][Batch 12499], Speed: 5.812 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.924,RCNNL1Loss=0.942 +[Epoch 2][Batch 12599], Speed: 6.267 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.203,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.924,RCNNL1Loss=0.942 +[Epoch 2][Batch 12699], Speed: 6.055 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.924,RCNNL1Loss=0.941 +[Epoch 2][Batch 12799], Speed: 5.510 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.924,RCNNL1Loss=0.941 +[Epoch 2][Batch 12899], Speed: 6.185 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.924,RCNNL1Loss=0.940 +[Epoch 2][Batch 12999], Speed: 5.762 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.924,RCNNL1Loss=0.940 +[Epoch 2][Batch 13099], Speed: 6.045 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.924,RCNNL1Loss=0.940 +[Epoch 2][Batch 13199], Speed: 5.664 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.303,RCNNAcc=0.925,RCNNL1Loss=0.939 +[Epoch 2][Batch 13299], Speed: 5.972 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.939 +[Epoch 2][Batch 13399], Speed: 6.254 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.938 +[Epoch 2][Batch 13499], Speed: 6.138 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.938 +[Epoch 2][Batch 13599], Speed: 5.923 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.938 +[Epoch 2][Batch 13699], Speed: 5.650 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.937 +[Epoch 2][Batch 13799], Speed: 5.928 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.937 +[Epoch 2][Batch 13899], Speed: 6.321 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.937 +[Epoch 2][Batch 13999], Speed: 5.850 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.936 +[Epoch 2][Batch 14099], Speed: 5.679 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.302,RCNNAcc=0.925,RCNNL1Loss=0.936 +[Epoch 2][Batch 14199], Speed: 5.803 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.936 +[Epoch 2][Batch 14299], Speed: 6.626 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.935 +[Epoch 2][Batch 14399], Speed: 6.062 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.935 +[Epoch 2][Batch 14499], Speed: 5.968 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.934 +[Epoch 2][Batch 14599], Speed: 5.728 samples/sec, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.934 +[Epoch 2] Training cost: 19727.295, RPN_Conf=0.033,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.202,RCNN_SmoothL1=0.258 +[Epoch 2] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.347 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.563 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.371 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.214 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.387 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.445 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.293 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.485 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.519 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.355 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.560 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.620 +person=50.8 +bicycle=23.5 +car=39.1 +motorcycle=38.4 +airplane=51.0 +bus=55.0 +train=52.8 +truck=30.7 +boat=21.2 +traffic light=25.1 +fire hydrant=60.2 +stop sign=55.2 +parking meter=36.9 +bench=19.4 +bird=32.5 +cat=54.5 +dog=54.6 +horse=46.5 +sheep=48.0 +cow=50.7 +elephant=57.3 +bear=62.0 +zebra=61.0 +giraffe=61.3 +backpack=14.1 +umbrella=33.6 +handbag=11.1 +tie=24.2 +suitcase=31.9 +frisbee=58.9 +skis=19.2 +snowboard=25.2 +sports ball=43.0 +kite=36.8 +baseball bat=21.9 +baseball glove=36.1 +skateboard=43.9 +surfboard=29.9 +tennis racket=39.2 +bottle=35.5 +wine glass=28.9 +cup=36.8 +fork=31.4 +knife=12.8 +spoon=10.1 +bowl=34.8 +banana=22.9 +apple=13.3 +sandwich=25.3 +orange=25.8 +broccoli=20.7 +carrot=17.8 +hot dog=24.9 +pizza=48.7 +donut=39.1 +cake=27.5 +chair=22.4 +couch=31.2 +potted plant=22.4 +bed=33.4 +dining table=18.7 +toilet=52.2 +tv=51.1 +laptop=53.6 +mouse=56.2 +remote=28.5 +keyboard=43.5 +cell phone=27.3 +microwave=45.4 +oven=30.1 +toaster=10.6 +sink=30.7 +refrigerator=41.2 +book=11.8 +clock=46.9 +vase=33.8 +scissors=23.1 +teddy bear=34.7 +hair drier=0.0 +toothbrush=13.3 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=34.7 +[Epoch 2] mAP 34.7 higher than current best [32.7] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 2] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0002_34.7000.params +[Epoch 3][Batch 99], Speed: 6.320 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.049,RCNN_CrossEntropy=0.195,RCNN_SmoothL1=0.251,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.933 +[Epoch 3][Batch 199], Speed: 6.898 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.189,RCNN_SmoothL1=0.246,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.933 +[Epoch 3][Batch 299], Speed: 5.901 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.186,RCNN_SmoothL1=0.245,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.932 +[Epoch 3][Batch 399], Speed: 6.230 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.186,RCNN_SmoothL1=0.247,RPNAcc=0.984,RPNL1Loss=0.301,RCNNAcc=0.925,RCNNL1Loss=0.932 +[Epoch 3][Batch 499], Speed: 5.906 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.048,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.932 +[Epoch 3][Batch 599], Speed: 6.409 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.931 +[Epoch 3][Batch 699], Speed: 6.409 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.186,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.931 +[Epoch 3][Batch 799], Speed: 5.990 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.930 +[Epoch 3][Batch 899], Speed: 6.004 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.930 +[Epoch 3][Batch 999], Speed: 6.345 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.930 +[Epoch 3][Batch 1099], Speed: 6.035 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.929 +[Epoch 3][Batch 1199], Speed: 5.816 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.929 +[Epoch 3][Batch 1299], Speed: 5.928 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.300,RCNNAcc=0.925,RCNNL1Loss=0.928 +[Epoch 3][Batch 1399], Speed: 5.877 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.928 +[Epoch 3][Batch 1499], Speed: 6.598 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.927 +[Epoch 3][Batch 1599], Speed: 6.203 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.927 +[Epoch 3][Batch 1699], Speed: 5.894 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.927 +[Epoch 3][Batch 1799], Speed: 6.088 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.926 +[Epoch 3][Batch 1899], Speed: 5.834 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.926 +[Epoch 3][Batch 1999], Speed: 6.401 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.925 +[Epoch 3][Batch 2099], Speed: 5.808 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.925 +[Epoch 3][Batch 2199], Speed: 6.521 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.299,RCNNAcc=0.925,RCNNL1Loss=0.925 +[Epoch 3][Batch 2299], Speed: 5.617 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.249,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.925,RCNNL1Loss=0.924 +[Epoch 3][Batch 2399], Speed: 5.911 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.925,RCNNL1Loss=0.924 +[Epoch 3][Batch 2499], Speed: 5.979 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.925,RCNNL1Loss=0.923 +[Epoch 3][Batch 2599], Speed: 5.828 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.925,RCNNL1Loss=0.923 +[Epoch 3][Batch 2699], Speed: 5.672 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.925,RCNNL1Loss=0.923 +[Epoch 3][Batch 2799], Speed: 6.487 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.925,RCNNL1Loss=0.922 +[Epoch 3][Batch 2899], Speed: 6.316 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.925,RCNNL1Loss=0.922 +[Epoch 3][Batch 2999], Speed: 5.599 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.926,RCNNL1Loss=0.921 +[Epoch 3][Batch 3099], Speed: 6.104 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.926,RCNNL1Loss=0.921 +[Epoch 3][Batch 3199], Speed: 6.067 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.298,RCNNAcc=0.926,RCNNL1Loss=0.921 +[Epoch 3][Batch 3299], Speed: 6.269 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.920 +[Epoch 3][Batch 3399], Speed: 5.900 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.920 +[Epoch 3][Batch 3499], Speed: 5.686 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.919 +[Epoch 3][Batch 3599], Speed: 5.600 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.919 +[Epoch 3][Batch 3699], Speed: 5.977 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.247,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.919 +[Epoch 3][Batch 3799], Speed: 6.438 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.918 +[Epoch 3][Batch 3899], Speed: 5.964 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.918 +[Epoch 3][Batch 3999], Speed: 5.981 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.918 +[Epoch 3][Batch 4099], Speed: 5.867 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.188,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.297,RCNNAcc=0.926,RCNNL1Loss=0.917 +[Epoch 3][Batch 4199], Speed: 5.635 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.189,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.917 +[Epoch 3][Batch 4299], Speed: 6.137 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.189,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.917 +[Epoch 3][Batch 4399], Speed: 5.049 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.189,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.916 +[Epoch 3][Batch 4499], Speed: 6.110 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.189,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.916 +[Epoch 3][Batch 4599], Speed: 5.981 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.916 +[Epoch 3][Batch 4699], Speed: 5.812 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.915 +[Epoch 3][Batch 4799], Speed: 5.652 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.915 +[Epoch 3][Batch 4899], Speed: 6.033 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.915 +[Epoch 3][Batch 4999], Speed: 5.560 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.914 +[Epoch 3][Batch 5099], Speed: 6.177 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.914 +[Epoch 3][Batch 5199], Speed: 5.635 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.296,RCNNAcc=0.926,RCNNL1Loss=0.913 +[Epoch 3][Batch 5299], Speed: 5.748 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.913 +[Epoch 3][Batch 5399], Speed: 5.890 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.913 +[Epoch 3][Batch 5499], Speed: 6.217 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.913 +[Epoch 3][Batch 5599], Speed: 5.665 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.912 +[Epoch 3][Batch 5699], Speed: 5.581 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.912 +[Epoch 3][Batch 5799], Speed: 5.873 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.912 +[Epoch 3][Batch 5899], Speed: 5.900 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.911 +[Epoch 3][Batch 5999], Speed: 6.194 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.911 +[Epoch 3][Batch 6099], Speed: 5.589 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.911 +[Epoch 3][Batch 6199], Speed: 5.650 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.910 +[Epoch 3][Batch 6299], Speed: 6.598 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.910 +[Epoch 3][Batch 6399], Speed: 5.682 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.295,RCNNAcc=0.926,RCNNL1Loss=0.910 +[Epoch 3][Batch 6499], Speed: 6.161 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.909 +[Epoch 3][Batch 6599], Speed: 6.004 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.909 +[Epoch 3][Batch 6699], Speed: 5.684 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.909 +[Epoch 3][Batch 6799], Speed: 5.870 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.908 +[Epoch 3][Batch 6899], Speed: 6.579 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.908 +[Epoch 3][Batch 6999], Speed: 5.577 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.908 +[Epoch 3][Batch 7099], Speed: 6.021 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.907 +[Epoch 3][Batch 7199], Speed: 5.688 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.907 +[Epoch 3][Batch 7299], Speed: 6.037 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.907 +[Epoch 3][Batch 7399], Speed: 5.825 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.906 +[Epoch 3][Batch 7499], Speed: 5.922 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.294,RCNNAcc=0.926,RCNNL1Loss=0.906 +[Epoch 3][Batch 7599], Speed: 5.586 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.906 +[Epoch 3][Batch 7699], Speed: 5.683 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.906 +[Epoch 3][Batch 7799], Speed: 5.481 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.905 +[Epoch 3][Batch 7899], Speed: 5.874 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.905 +[Epoch 3][Batch 7999], Speed: 5.608 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.984,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.905 +[Epoch 3][Batch 8099], Speed: 5.904 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.904 +[Epoch 3][Batch 8199], Speed: 5.790 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.904 +[Epoch 3][Batch 8299], Speed: 6.083 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.904 +[Epoch 3][Batch 8399], Speed: 6.212 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.903 +[Epoch 3][Batch 8499], Speed: 5.380 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.293,RCNNAcc=0.926,RCNNL1Loss=0.903 +[Epoch 3][Batch 8599], Speed: 5.904 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.293,RCNNAcc=0.927,RCNNL1Loss=0.903 +[Epoch 3][Batch 8699], Speed: 6.347 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.293,RCNNAcc=0.927,RCNNL1Loss=0.902 +[Epoch 3][Batch 8799], Speed: 6.298 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.902 +[Epoch 3][Batch 8899], Speed: 6.044 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.902 +[Epoch 3][Batch 8999], Speed: 6.105 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.902 +[Epoch 3][Batch 9099], Speed: 5.623 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.901 +[Epoch 3][Batch 9199], Speed: 6.118 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.901 +[Epoch 3][Batch 9299], Speed: 6.062 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.901 +[Epoch 3][Batch 9399], Speed: 5.739 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.900 +[Epoch 3][Batch 9499], Speed: 5.327 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.900 +[Epoch 3][Batch 9599], Speed: 5.778 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.900 +[Epoch 3][Batch 9699], Speed: 5.639 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.900 +[Epoch 3][Batch 9799], Speed: 6.019 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.899 +[Epoch 3][Batch 9899], Speed: 5.953 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.899 +[Epoch 3][Batch 9999], Speed: 6.341 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.292,RCNNAcc=0.927,RCNNL1Loss=0.899 +[Epoch 3][Batch 10099], Speed: 5.960 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.898 +[Epoch 3][Batch 10199], Speed: 5.831 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.898 +[Epoch 3][Batch 10299], Speed: 5.893 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.898 +[Epoch 3][Batch 10399], Speed: 5.983 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.898 +[Epoch 3][Batch 10499], Speed: 5.137 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.897 +[Epoch 3][Batch 10599], Speed: 5.972 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.897 +[Epoch 3][Batch 10699], Speed: 6.618 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.897 +[Epoch 3][Batch 10799], Speed: 6.451 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.896 +[Epoch 3][Batch 10899], Speed: 6.126 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.248,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.896 +[Epoch 3][Batch 10999], Speed: 6.042 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.896 +[Epoch 3][Batch 11099], Speed: 5.982 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.896 +[Epoch 3][Batch 11199], Speed: 6.498 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.895 +[Epoch 3][Batch 11299], Speed: 5.687 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.291,RCNNAcc=0.927,RCNNL1Loss=0.895 +[Epoch 3][Batch 11399], Speed: 6.258 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.895 +[Epoch 3][Batch 11499], Speed: 6.117 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.894 +[Epoch 3][Batch 11599], Speed: 6.039 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.894 +[Epoch 3][Batch 11699], Speed: 5.993 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.894 +[Epoch 3][Batch 11799], Speed: 5.612 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.894 +[Epoch 3][Batch 11899], Speed: 5.509 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.893 +[Epoch 3][Batch 11999], Speed: 6.056 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.893 +[Epoch 3][Batch 12099], Speed: 5.631 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.893 +[Epoch 3][Batch 12199], Speed: 5.579 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.892 +[Epoch 3][Batch 12299], Speed: 5.678 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.892 +[Epoch 3][Batch 12399], Speed: 6.031 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.892 +[Epoch 3][Batch 12499], Speed: 5.441 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.290,RCNNAcc=0.927,RCNNL1Loss=0.892 +[Epoch 3][Batch 12599], Speed: 5.680 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.891 +[Epoch 3][Batch 12699], Speed: 5.879 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.891 +[Epoch 3][Batch 12799], Speed: 6.248 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.891 +[Epoch 3][Batch 12899], Speed: 5.944 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.891 +[Epoch 3][Batch 12999], Speed: 6.143 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.890 +[Epoch 3][Batch 13099], Speed: 5.555 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.890 +[Epoch 3][Batch 13199], Speed: 6.061 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.890 +[Epoch 3][Batch 13299], Speed: 5.888 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.890 +[Epoch 3][Batch 13399], Speed: 6.185 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.889 +[Epoch 3][Batch 13499], Speed: 6.267 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.889 +[Epoch 3][Batch 13599], Speed: 5.727 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.889 +[Epoch 3][Batch 13699], Speed: 6.183 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.889 +[Epoch 3][Batch 13799], Speed: 6.196 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.888 +[Epoch 3][Batch 13899], Speed: 6.172 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.289,RCNNAcc=0.927,RCNNL1Loss=0.888 +[Epoch 3][Batch 13999], Speed: 5.488 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.888 +[Epoch 3][Batch 14099], Speed: 6.124 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.888 +[Epoch 3][Batch 14199], Speed: 6.109 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.887 +[Epoch 3][Batch 14299], Speed: 5.637 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.887 +[Epoch 3][Batch 14399], Speed: 6.172 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.192,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.887 +[Epoch 3][Batch 14499], Speed: 5.637 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.887 +[Epoch 3][Batch 14599], Speed: 5.721 samples/sec, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.886 +[Epoch 3] Training cost: 19769.544, RPN_Conf=0.031,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.191,RCNN_SmoothL1=0.247 +[Epoch 3] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.350 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.564 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.380 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.228 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.393 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.447 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.301 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.492 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.523 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.358 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.569 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.635 +person=51.4 +bicycle=28.1 +car=38.3 +motorcycle=36.0 +airplane=56.1 +bus=56.5 +train=50.7 +truck=26.3 +boat=23.6 +traffic light=25.1 +fire hydrant=57.9 +stop sign=61.6 +parking meter=38.4 +bench=19.1 +bird=32.1 +cat=62.4 +dog=53.5 +horse=48.6 +sheep=48.6 +cow=48.1 +elephant=54.3 +bear=62.3 +zebra=59.0 +giraffe=54.5 +backpack=13.6 +umbrella=31.2 +handbag=11.9 +tie=26.7 +suitcase=36.5 +frisbee=60.0 +skis=18.7 +snowboard=29.2 +sports ball=39.4 +kite=38.1 +baseball bat=27.1 +baseball glove=33.9 +skateboard=49.7 +surfboard=32.5 +tennis racket=42.1 +bottle=36.4 +wine glass=32.8 +cup=39.9 +fork=33.4 +knife=16.1 +spoon=12.4 +bowl=33.0 +banana=20.4 +apple=15.8 +sandwich=16.5 +orange=22.2 +broccoli=19.7 +carrot=20.3 +hot dog=19.7 +pizza=41.3 +donut=27.3 +cake=24.8 +chair=23.8 +couch=31.7 +potted plant=20.2 +bed=33.7 +dining table=21.2 +toilet=53.1 +tv=49.6 +laptop=53.1 +mouse=53.0 +remote=28.2 +keyboard=41.4 +cell phone=33.0 +microwave=50.4 +oven=28.2 +toaster=19.6 +sink=31.3 +refrigerator=41.7 +book=15.3 +clock=49.1 +vase=34.8 +scissors=22.4 +teddy bear=33.5 +hair drier=0.0 +toothbrush=18.2 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=35.0 +[Epoch 3] mAP 35.0 higher than current best [34.7] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 3] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0003_35.0000.params +[Epoch 4][Batch 99], Speed: 6.212 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.190,RCNN_SmoothL1=0.242,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.886 +[Epoch 4][Batch 199], Speed: 6.391 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.187,RCNN_SmoothL1=0.242,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.885 +[Epoch 4][Batch 299], Speed: 6.539 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.885 +[Epoch 4][Batch 399], Speed: 5.680 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.885 +[Epoch 4][Batch 499], Speed: 6.223 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.288,RCNNAcc=0.927,RCNNL1Loss=0.885 +[Epoch 4][Batch 599], Speed: 5.938 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.884 +[Epoch 4][Batch 699], Speed: 5.692 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.884 +[Epoch 4][Batch 799], Speed: 5.730 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.884 +[Epoch 4][Batch 899], Speed: 5.807 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.883 +[Epoch 4][Batch 999], Speed: 5.893 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.883 +[Epoch 4][Batch 1099], Speed: 5.824 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.236,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.883 +[Epoch 4][Batch 1199], Speed: 5.916 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.883 +[Epoch 4][Batch 1299], Speed: 5.786 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.882 +[Epoch 4][Batch 1399], Speed: 5.870 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.882 +[Epoch 4][Batch 1499], Speed: 6.217 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.882 +[Epoch 4][Batch 1599], Speed: 6.983 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.237,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.881 +[Epoch 4][Batch 1699], Speed: 6.007 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.881 +[Epoch 4][Batch 1799], Speed: 5.984 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.287,RCNNAcc=0.928,RCNNL1Loss=0.881 +[Epoch 4][Batch 1899], Speed: 5.782 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.881 +[Epoch 4][Batch 1999], Speed: 6.056 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.880 +[Epoch 4][Batch 2099], Speed: 5.611 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.880 +[Epoch 4][Batch 2199], Speed: 6.342 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.880 +[Epoch 4][Batch 2299], Speed: 5.490 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.879 +[Epoch 4][Batch 2399], Speed: 6.191 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.879 +[Epoch 4][Batch 2499], Speed: 5.903 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.879 +[Epoch 4][Batch 2599], Speed: 6.090 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.879 +[Epoch 4][Batch 2699], Speed: 5.998 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.238,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.878 +[Epoch 4][Batch 2799], Speed: 5.875 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.179,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.878 +[Epoch 4][Batch 2899], Speed: 6.141 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.180,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.878 +[Epoch 4][Batch 2999], Speed: 5.758 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.180,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.878 +[Epoch 4][Batch 3099], Speed: 5.542 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.180,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.877 +[Epoch 4][Batch 3199], Speed: 5.769 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.180,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.286,RCNNAcc=0.928,RCNNL1Loss=0.877 +[Epoch 4][Batch 3299], Speed: 5.910 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.180,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.877 +[Epoch 4][Batch 3399], Speed: 6.039 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.180,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.876 +[Epoch 4][Batch 3499], Speed: 5.476 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.180,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.876 +[Epoch 4][Batch 3599], Speed: 5.600 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.181,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.876 +[Epoch 4][Batch 3699], Speed: 5.673 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.181,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.876 +[Epoch 4][Batch 3799], Speed: 5.765 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.181,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.875 +[Epoch 4][Batch 3899], Speed: 5.756 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.181,RCNN_SmoothL1=0.239,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.875 +[Epoch 4][Batch 3999], Speed: 5.668 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.181,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.875 +[Epoch 4][Batch 4099], Speed: 5.830 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.875 +[Epoch 4][Batch 4199], Speed: 6.029 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.874 +[Epoch 4][Batch 4299], Speed: 5.415 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.874 +[Epoch 4][Batch 4399], Speed: 6.250 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.874 +[Epoch 4][Batch 4499], Speed: 5.722 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.874 +[Epoch 4][Batch 4599], Speed: 5.671 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.285,RCNNAcc=0.928,RCNNL1Loss=0.874 +[Epoch 4][Batch 4699], Speed: 5.870 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.873 +[Epoch 4][Batch 4799], Speed: 6.134 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.873 +[Epoch 4][Batch 4899], Speed: 5.704 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.873 +[Epoch 4][Batch 4999], Speed: 5.265 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.872 +[Epoch 4][Batch 5099], Speed: 5.611 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.872 +[Epoch 4][Batch 5199], Speed: 6.101 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.872 +[Epoch 4][Batch 5299], Speed: 6.614 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.872 +[Epoch 4][Batch 5399], Speed: 6.226 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.872 +[Epoch 4][Batch 5499], Speed: 5.710 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.871 +[Epoch 4][Batch 5599], Speed: 5.661 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.871 +[Epoch 4][Batch 5699], Speed: 5.501 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.871 +[Epoch 4][Batch 5799], Speed: 6.000 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.871 +[Epoch 4][Batch 5899], Speed: 6.148 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.870 +[Epoch 4][Batch 5999], Speed: 5.785 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.870 +[Epoch 4][Batch 6099], Speed: 6.202 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.182,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.284,RCNNAcc=0.928,RCNNL1Loss=0.870 +[Epoch 4][Batch 6199], Speed: 5.793 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.870 +[Epoch 4][Batch 6299], Speed: 5.814 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.869 +[Epoch 4][Batch 6399], Speed: 6.284 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.869 +[Epoch 4][Batch 6499], Speed: 5.716 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.869 +[Epoch 4][Batch 6599], Speed: 5.696 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.869 +[Epoch 4][Batch 6699], Speed: 5.986 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.868 +[Epoch 4][Batch 6799], Speed: 6.016 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.868 +[Epoch 4][Batch 6899], Speed: 6.634 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.868 +[Epoch 4][Batch 6999], Speed: 6.043 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.868 +[Epoch 4][Batch 7099], Speed: 5.630 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.868 +[Epoch 4][Batch 7199], Speed: 5.959 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.928,RCNNL1Loss=0.867 +[Epoch 4][Batch 7299], Speed: 5.975 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.929,RCNNL1Loss=0.867 +[Epoch 4][Batch 7399], Speed: 5.680 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.929,RCNNL1Loss=0.867 +[Epoch 4][Batch 7499], Speed: 6.103 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.929,RCNNL1Loss=0.867 +[Epoch 4][Batch 7599], Speed: 6.286 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.929,RCNNL1Loss=0.866 +[Epoch 4][Batch 7699], Speed: 6.001 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.283,RCNNAcc=0.929,RCNNL1Loss=0.866 +[Epoch 4][Batch 7799], Speed: 6.017 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.866 +[Epoch 4][Batch 7899], Speed: 5.681 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.866 +[Epoch 4][Batch 7999], Speed: 5.557 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.866 +[Epoch 4][Batch 8099], Speed: 5.699 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.865 +[Epoch 4][Batch 8199], Speed: 5.615 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.865 +[Epoch 4][Batch 8299], Speed: 5.834 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.865 +[Epoch 4][Batch 8399], Speed: 5.963 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.865 +[Epoch 4][Batch 8499], Speed: 5.427 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.864 +[Epoch 4][Batch 8599], Speed: 5.842 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.864 +[Epoch 4][Batch 8699], Speed: 6.040 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.864 +[Epoch 4][Batch 8799], Speed: 6.274 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.864 +[Epoch 4][Batch 8899], Speed: 6.316 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.864 +[Epoch 4][Batch 8999], Speed: 5.838 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.863 +[Epoch 4][Batch 9099], Speed: 6.373 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.863 +[Epoch 4][Batch 9199], Speed: 5.790 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.863 +[Epoch 4][Batch 9299], Speed: 5.676 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.282,RCNNAcc=0.929,RCNNL1Loss=0.863 +[Epoch 4][Batch 9399], Speed: 5.810 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.863 +[Epoch 4][Batch 9499], Speed: 5.770 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.862 +[Epoch 4][Batch 9599], Speed: 5.954 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.862 +[Epoch 4][Batch 9699], Speed: 6.534 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.862 +[Epoch 4][Batch 9799], Speed: 5.994 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.985,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.862 +[Epoch 4][Batch 9899], Speed: 6.031 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.861 +[Epoch 4][Batch 9999], Speed: 5.598 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.861 +[Epoch 4][Batch 10099], Speed: 5.613 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.861 +[Epoch 4][Batch 10199], Speed: 6.273 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.861 +[Epoch 4][Batch 10299], Speed: 5.605 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.861 +[Epoch 4][Batch 10399], Speed: 5.584 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.860 +[Epoch 4][Batch 10499], Speed: 6.075 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.860 +[Epoch 4][Batch 10599], Speed: 6.131 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.860 +[Epoch 4][Batch 10699], Speed: 5.701 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.183,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.860 +[Epoch 4][Batch 10799], Speed: 5.234 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.859 +[Epoch 4][Batch 10899], Speed: 6.198 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.281,RCNNAcc=0.929,RCNNL1Loss=0.859 +[Epoch 4][Batch 10999], Speed: 5.913 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.859 +[Epoch 4][Batch 11099], Speed: 6.178 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.859 +[Epoch 4][Batch 11199], Speed: 5.731 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.240,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.859 +[Epoch 4][Batch 11299], Speed: 6.003 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.858 +[Epoch 4][Batch 11399], Speed: 5.903 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.858 +[Epoch 4][Batch 11499], Speed: 6.009 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.858 +[Epoch 4][Batch 11599], Speed: 6.156 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.858 +[Epoch 4][Batch 11699], Speed: 5.822 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.858 +[Epoch 4][Batch 11799], Speed: 5.481 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.858 +[Epoch 4][Batch 11899], Speed: 6.079 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.857 +[Epoch 4][Batch 11999], Speed: 6.380 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.857 +[Epoch 4][Batch 12099], Speed: 6.110 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.857 +[Epoch 4][Batch 12199], Speed: 6.017 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.857 +[Epoch 4][Batch 12299], Speed: 5.552 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.857 +[Epoch 4][Batch 12399], Speed: 5.613 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.856 +[Epoch 4][Batch 12499], Speed: 6.160 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.856 +[Epoch 4][Batch 12599], Speed: 5.966 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.856 +[Epoch 4][Batch 12699], Speed: 6.038 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.856 +[Epoch 4][Batch 12799], Speed: 6.686 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.280,RCNNAcc=0.929,RCNNL1Loss=0.856 +[Epoch 4][Batch 12899], Speed: 6.022 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.855 +[Epoch 4][Batch 12999], Speed: 5.591 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.855 +[Epoch 4][Batch 13099], Speed: 6.047 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.855 +[Epoch 4][Batch 13199], Speed: 5.656 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.855 +[Epoch 4][Batch 13299], Speed: 6.198 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.855 +[Epoch 4][Batch 13399], Speed: 6.033 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.855 +[Epoch 4][Batch 13499], Speed: 6.558 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.854 +[Epoch 4][Batch 13599], Speed: 5.485 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.854 +[Epoch 4][Batch 13699], Speed: 6.223 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.854 +[Epoch 4][Batch 13799], Speed: 6.157 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.854 +[Epoch 4][Batch 13899], Speed: 5.830 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.854 +[Epoch 4][Batch 13999], Speed: 5.379 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.853 +[Epoch 4][Batch 14099], Speed: 5.694 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.853 +[Epoch 4][Batch 14199], Speed: 6.001 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.853 +[Epoch 4][Batch 14299], Speed: 6.135 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.853 +[Epoch 4][Batch 14399], Speed: 6.030 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.853 +[Epoch 4][Batch 14499], Speed: 5.657 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.853 +[Epoch 4][Batch 14599], Speed: 6.018 samples/sec, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239,RPNAcc=0.986,RPNL1Loss=0.279,RCNNAcc=0.929,RCNNL1Loss=0.852 +[Epoch 4] Training cost: 19849.423, RPN_Conf=0.030,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.184,RCNN_SmoothL1=0.239 +[Epoch 4] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.367 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.583 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.401 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.229 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.412 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.468 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.305 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.497 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.528 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.358 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.571 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.644 +person=51.5 +bicycle=28.4 +car=40.9 +motorcycle=36.1 +airplane=55.2 +bus=59.0 +train=55.9 +truck=31.2 +boat=23.2 +traffic light=24.4 +fire hydrant=65.7 +stop sign=60.6 +parking meter=40.8 +bench=20.9 +bird=34.0 +cat=63.9 +dog=52.6 +horse=49.7 +sheep=44.7 +cow=51.8 +elephant=50.3 +bear=62.0 +zebra=58.7 +giraffe=56.8 +backpack=14.3 +umbrella=35.0 +handbag=13.1 +tie=29.2 +suitcase=32.7 +frisbee=58.5 +skis=18.1 +snowboard=30.5 +sports ball=41.6 +kite=35.8 +baseball bat=26.0 +baseball glove=36.8 +skateboard=46.5 +surfboard=34.2 +tennis racket=40.1 +bottle=37.4 +wine glass=31.6 +cup=38.4 +fork=32.3 +knife=18.4 +spoon=15.9 +bowl=35.6 +banana=21.0 +apple=14.3 +sandwich=26.6 +orange=24.8 +broccoli=15.1 +carrot=19.6 +hot dog=31.5 +pizza=49.2 +donut=35.9 +cake=30.1 +chair=24.8 +couch=36.3 +potted plant=22.1 +bed=31.0 +dining table=21.7 +toilet=49.4 +tv=53.1 +laptop=56.8 +mouse=56.0 +remote=34.1 +keyboard=48.6 +cell phone=33.0 +microwave=53.1 +oven=30.3 +toaster=43.2 +sink=34.4 +refrigerator=47.9 +book=12.5 +clock=45.7 +vase=34.6 +scissors=21.1 +teddy bear=34.9 +hair drier=0.0 +toothbrush=20.0 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=36.7 +[Epoch 4] mAP 36.7 higher than current best [35.0] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 4] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0004_36.7000.params +[Epoch 5][Batch 99], Speed: 6.507 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.852 +[Epoch 5][Batch 199], Speed: 6.790 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.852 +[Epoch 5][Batch 299], Speed: 6.695 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.852 +[Epoch 5][Batch 399], Speed: 6.210 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.851 +[Epoch 5][Batch 499], Speed: 6.328 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.236,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.851 +[Epoch 5][Batch 599], Speed: 5.984 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.851 +[Epoch 5][Batch 699], Speed: 5.879 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.851 +[Epoch 5][Batch 799], Speed: 6.303 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.237,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.851 +[Epoch 5][Batch 899], Speed: 5.728 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.047,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.236,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.850 +[Epoch 5][Batch 999], Speed: 5.824 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.236,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.929,RCNNL1Loss=0.850 +[Epoch 5][Batch 1099], Speed: 5.807 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.236,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.930,RCNNL1Loss=0.850 +[Epoch 5][Batch 1199], Speed: 5.695 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.930,RCNNL1Loss=0.850 +[Epoch 5][Batch 1299], Speed: 6.128 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.930,RCNNL1Loss=0.850 +[Epoch 5][Batch 1399], Speed: 6.010 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.930,RCNNL1Loss=0.849 +[Epoch 5][Batch 1499], Speed: 6.286 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.930,RCNNL1Loss=0.849 +[Epoch 5][Batch 1599], Speed: 5.762 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.278,RCNNAcc=0.930,RCNNL1Loss=0.849 +[Epoch 5][Batch 1699], Speed: 5.788 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.849 +[Epoch 5][Batch 1799], Speed: 5.625 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.848 +[Epoch 5][Batch 1899], Speed: 6.201 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.848 +[Epoch 5][Batch 1999], Speed: 5.692 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.848 +[Epoch 5][Batch 2099], Speed: 6.188 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.848 +[Epoch 5][Batch 2199], Speed: 5.684 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.848 +[Epoch 5][Batch 2299], Speed: 5.766 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.847 +[Epoch 5][Batch 2399], Speed: 5.756 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.847 +[Epoch 5][Batch 2499], Speed: 6.297 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.847 +[Epoch 5][Batch 2599], Speed: 6.184 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.847 +[Epoch 5][Batch 2699], Speed: 5.479 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.847 +[Epoch 5][Batch 2799], Speed: 6.156 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.846 +[Epoch 5][Batch 2899], Speed: 5.830 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.846 +[Epoch 5][Batch 2999], Speed: 5.995 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.846 +[Epoch 5][Batch 3099], Speed: 6.248 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.846 +[Epoch 5][Batch 3199], Speed: 5.197 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.846 +[Epoch 5][Batch 3299], Speed: 5.944 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.277,RCNNAcc=0.930,RCNNL1Loss=0.845 +[Epoch 5][Batch 3399], Speed: 5.682 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.175,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.845 +[Epoch 5][Batch 3499], Speed: 6.016 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.845 +[Epoch 5][Batch 3599], Speed: 6.554 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.845 +[Epoch 5][Batch 3699], Speed: 6.051 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.845 +[Epoch 5][Batch 3799], Speed: 6.069 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.845 +[Epoch 5][Batch 3899], Speed: 6.183 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.844 +[Epoch 5][Batch 3999], Speed: 5.817 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.844 +[Epoch 5][Batch 4099], Speed: 5.145 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.844 +[Epoch 5][Batch 4199], Speed: 6.085 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.844 +[Epoch 5][Batch 4299], Speed: 5.966 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.844 +[Epoch 5][Batch 4399], Speed: 5.611 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.843 +[Epoch 5][Batch 4499], Speed: 6.103 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.843 +[Epoch 5][Batch 4599], Speed: 6.076 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.843 +[Epoch 5][Batch 4699], Speed: 6.352 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.843 +[Epoch 5][Batch 4799], Speed: 6.448 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.843 +[Epoch 5][Batch 4899], Speed: 5.608 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.842 +[Epoch 5][Batch 4999], Speed: 5.774 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.842 +[Epoch 5][Batch 5099], Speed: 5.881 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.842 +[Epoch 5][Batch 5199], Speed: 5.833 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.276,RCNNAcc=0.930,RCNNL1Loss=0.842 +[Epoch 5][Batch 5299], Speed: 6.176 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.842 +[Epoch 5][Batch 5399], Speed: 5.729 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.842 +[Epoch 5][Batch 5499], Speed: 5.239 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.841 +[Epoch 5][Batch 5599], Speed: 5.515 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.841 +[Epoch 5][Batch 5699], Speed: 5.909 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.841 +[Epoch 5][Batch 5799], Speed: 6.307 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.841 +[Epoch 5][Batch 5899], Speed: 5.770 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.176,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.841 +[Epoch 5][Batch 5999], Speed: 6.067 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.840 +[Epoch 5][Batch 6099], Speed: 6.026 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.840 +[Epoch 5][Batch 6199], Speed: 6.072 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.840 +[Epoch 5][Batch 6299], Speed: 6.287 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.840 +[Epoch 5][Batch 6399], Speed: 5.996 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.840 +[Epoch 5][Batch 6499], Speed: 5.971 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.840 +[Epoch 5][Batch 6599], Speed: 5.821 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.839 +[Epoch 5][Batch 6699], Speed: 5.737 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.839 +[Epoch 5][Batch 6799], Speed: 6.219 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.839 +[Epoch 5][Batch 6899], Speed: 6.346 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.839 +[Epoch 5][Batch 6999], Speed: 5.455 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.839 +[Epoch 5][Batch 7099], Speed: 6.130 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.839 +[Epoch 5][Batch 7199], Speed: 6.373 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.275,RCNNAcc=0.930,RCNNL1Loss=0.838 +[Epoch 5][Batch 7299], Speed: 5.943 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.838 +[Epoch 5][Batch 7399], Speed: 5.217 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.838 +[Epoch 5][Batch 7499], Speed: 6.429 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.838 +[Epoch 5][Batch 7599], Speed: 5.059 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.838 +[Epoch 5][Batch 7699], Speed: 5.412 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.838 +[Epoch 5][Batch 7799], Speed: 6.034 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.837 +[Epoch 5][Batch 7899], Speed: 6.129 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.837 +[Epoch 5][Batch 7999], Speed: 5.678 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.837 +[Epoch 5][Batch 8099], Speed: 6.057 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.837 +[Epoch 5][Batch 8199], Speed: 5.600 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.837 +[Epoch 5][Batch 8299], Speed: 6.114 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.837 +[Epoch 5][Batch 8399], Speed: 5.799 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.836 +[Epoch 5][Batch 8499], Speed: 5.960 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.836 +[Epoch 5][Batch 8599], Speed: 6.358 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.836 +[Epoch 5][Batch 8699], Speed: 5.755 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.836 +[Epoch 5][Batch 8799], Speed: 5.488 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.836 +[Epoch 5][Batch 8899], Speed: 5.862 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.835 +[Epoch 5][Batch 8999], Speed: 5.938 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.835 +[Epoch 5][Batch 9099], Speed: 5.578 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.835 +[Epoch 5][Batch 9199], Speed: 6.002 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.274,RCNNAcc=0.930,RCNNL1Loss=0.835 +[Epoch 5][Batch 9299], Speed: 5.376 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.930,RCNNL1Loss=0.835 +[Epoch 5][Batch 9399], Speed: 6.247 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.930,RCNNL1Loss=0.835 +[Epoch 5][Batch 9499], Speed: 6.095 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.930,RCNNL1Loss=0.835 +[Epoch 5][Batch 9599], Speed: 5.912 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.930,RCNNL1Loss=0.834 +[Epoch 5][Batch 9699], Speed: 5.213 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.834 +[Epoch 5][Batch 9799], Speed: 5.646 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.834 +[Epoch 5][Batch 9899], Speed: 5.434 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.834 +[Epoch 5][Batch 9999], Speed: 5.274 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.834 +[Epoch 5][Batch 10099], Speed: 5.525 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.834 +[Epoch 5][Batch 10199], Speed: 6.393 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.833 +[Epoch 5][Batch 10299], Speed: 5.297 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.833 +[Epoch 5][Batch 10399], Speed: 5.542 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.833 +[Epoch 5][Batch 10499], Speed: 6.561 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.833 +[Epoch 5][Batch 10599], Speed: 5.673 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.833 +[Epoch 5][Batch 10699], Speed: 5.436 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.833 +[Epoch 5][Batch 10799], Speed: 5.965 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.832 +[Epoch 5][Batch 10899], Speed: 6.238 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.832 +[Epoch 5][Batch 10999], Speed: 6.248 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.832 +[Epoch 5][Batch 11099], Speed: 5.819 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.832 +[Epoch 5][Batch 11199], Speed: 5.809 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.832 +[Epoch 5][Batch 11299], Speed: 5.262 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.832 +[Epoch 5][Batch 11399], Speed: 5.960 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.273,RCNNAcc=0.931,RCNNL1Loss=0.832 +[Epoch 5][Batch 11499], Speed: 5.943 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.831 +[Epoch 5][Batch 11599], Speed: 6.095 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.234,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.831 +[Epoch 5][Batch 11699], Speed: 5.695 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.831 +[Epoch 5][Batch 11799], Speed: 5.641 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.831 +[Epoch 5][Batch 11899], Speed: 6.232 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.831 +[Epoch 5][Batch 11999], Speed: 5.586 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.831 +[Epoch 5][Batch 12099], Speed: 6.025 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.830 +[Epoch 5][Batch 12199], Speed: 6.321 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.830 +[Epoch 5][Batch 12299], Speed: 5.974 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.830 +[Epoch 5][Batch 12399], Speed: 6.139 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.830 +[Epoch 5][Batch 12499], Speed: 6.153 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.830 +[Epoch 5][Batch 12599], Speed: 5.647 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.830 +[Epoch 5][Batch 12699], Speed: 5.820 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.830 +[Epoch 5][Batch 12799], Speed: 6.143 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.829 +[Epoch 5][Batch 12899], Speed: 6.066 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.829 +[Epoch 5][Batch 12999], Speed: 5.495 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.829 +[Epoch 5][Batch 13099], Speed: 6.194 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.829 +[Epoch 5][Batch 13199], Speed: 6.011 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.829 +[Epoch 5][Batch 13299], Speed: 5.542 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.829 +[Epoch 5][Batch 13399], Speed: 5.602 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.828 +[Epoch 5][Batch 13499], Speed: 6.403 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.828 +[Epoch 5][Batch 13599], Speed: 5.854 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.828 +[Epoch 5][Batch 13699], Speed: 6.288 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.272,RCNNAcc=0.931,RCNNL1Loss=0.828 +[Epoch 5][Batch 13799], Speed: 5.825 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.828 +[Epoch 5][Batch 13899], Speed: 6.050 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.828 +[Epoch 5][Batch 13999], Speed: 5.891 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.828 +[Epoch 5][Batch 14099], Speed: 6.218 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.827 +[Epoch 5][Batch 14199], Speed: 5.819 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.827 +[Epoch 5][Batch 14299], Speed: 5.622 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.827 +[Epoch 5][Batch 14399], Speed: 6.032 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.827 +[Epoch 5][Batch 14499], Speed: 5.281 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.827 +[Epoch 5][Batch 14599], Speed: 6.088 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.827 +[Epoch 5] Training cost: 19896.970, RPN_Conf=0.029,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.178,RCNN_SmoothL1=0.233 +[Epoch 5] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.375 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.585 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.405 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.231 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.420 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.466 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.310 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.509 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.544 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.371 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.588 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.650 +person=51.8 +bicycle=29.5 +car=42.7 +motorcycle=40.0 +airplane=59.5 +bus=61.8 +train=58.5 +truck=30.5 +boat=20.5 +traffic light=24.4 +fire hydrant=63.5 +stop sign=62.9 +parking meter=45.3 +bench=20.4 +bird=30.4 +cat=58.5 +dog=60.1 +horse=52.4 +sheep=49.5 +cow=47.5 +elephant=57.6 +bear=58.3 +zebra=62.0 +giraffe=62.0 +backpack=13.8 +umbrella=35.1 +handbag=14.1 +tie=30.8 +suitcase=31.3 +frisbee=60.2 +skis=19.4 +snowboard=32.8 +sports ball=42.4 +kite=39.4 +baseball bat=29.1 +baseball glove=38.6 +skateboard=50.3 +surfboard=34.1 +tennis racket=46.4 +bottle=37.7 +wine glass=34.0 +cup=41.4 +fork=29.9 +knife=15.0 +spoon=18.0 +bowl=36.5 +banana=21.1 +apple=17.1 +sandwich=23.4 +orange=24.7 +broccoli=17.2 +carrot=19.4 +hot dog=32.2 +pizza=48.4 +donut=44.1 +cake=31.3 +chair=24.0 +couch=34.1 +potted plant=24.9 +bed=34.8 +dining table=22.4 +toilet=55.6 +tv=51.5 +laptop=58.9 +mouse=52.2 +remote=32.0 +keyboard=48.2 +cell phone=31.8 +microwave=41.8 +oven=30.5 +toaster=34.3 +sink=33.0 +refrigerator=48.0 +book=11.7 +clock=50.1 +vase=36.6 +scissors=25.0 +teddy bear=38.9 +hair drier=0.0 +toothbrush=22.1 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.5 +[Epoch 5] mAP 37.5 higher than current best [36.7] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 5] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0005_37.5000.params +[Epoch 6][Batch 99], Speed: 6.006 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.827 +[Epoch 6][Batch 199], Speed: 6.596 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.235,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.826 +[Epoch 6][Batch 299], Speed: 6.103 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.826 +[Epoch 6][Batch 399], Speed: 6.674 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.826 +[Epoch 6][Batch 499], Speed: 6.175 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.826 +[Epoch 6][Batch 599], Speed: 5.887 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.229,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.826 +[Epoch 6][Batch 699], Speed: 6.065 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.229,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.825 +[Epoch 6][Batch 799], Speed: 6.001 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.229,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.825 +[Epoch 6][Batch 899], Speed: 6.336 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.228,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.825 +[Epoch 6][Batch 999], Speed: 5.735 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.227,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.825 +[Epoch 6][Batch 1099], Speed: 5.819 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.228,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.825 +[Epoch 6][Batch 1199], Speed: 5.881 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.229,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.825 +[Epoch 6][Batch 1299], Speed: 6.480 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.229,RPNAcc=0.986,RPNL1Loss=0.271,RCNNAcc=0.931,RCNNL1Loss=0.824 +[Epoch 6][Batch 1399], Speed: 5.992 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.824 +[Epoch 6][Batch 1499], Speed: 5.691 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.824 +[Epoch 6][Batch 1599], Speed: 5.525 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.824 +[Epoch 6][Batch 1699], Speed: 5.947 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.824 +[Epoch 6][Batch 1799], Speed: 5.621 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.824 +[Epoch 6][Batch 1899], Speed: 5.944 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.823 +[Epoch 6][Batch 1999], Speed: 6.445 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.823 +[Epoch 6][Batch 2099], Speed: 5.845 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.823 +[Epoch 6][Batch 2199], Speed: 5.791 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.823 +[Epoch 6][Batch 2299], Speed: 5.520 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.823 +[Epoch 6][Batch 2399], Speed: 6.235 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.823 +[Epoch 6][Batch 2499], Speed: 5.936 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.822 +[Epoch 6][Batch 2599], Speed: 6.143 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.822 +[Epoch 6][Batch 2699], Speed: 6.052 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.822 +[Epoch 6][Batch 2799], Speed: 6.239 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.822 +[Epoch 6][Batch 2899], Speed: 5.275 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.822 +[Epoch 6][Batch 2999], Speed: 5.920 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.822 +[Epoch 6][Batch 3099], Speed: 5.320 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.822 +[Epoch 6][Batch 3199], Speed: 6.085 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.821 +[Epoch 6][Batch 3299], Speed: 6.008 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.821 +[Epoch 6][Batch 3399], Speed: 5.711 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.821 +[Epoch 6][Batch 3499], Speed: 5.901 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.270,RCNNAcc=0.931,RCNNL1Loss=0.821 +[Epoch 6][Batch 3599], Speed: 6.013 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.231,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.821 +[Epoch 6][Batch 3699], Speed: 5.788 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.821 +[Epoch 6][Batch 3799], Speed: 5.710 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.821 +[Epoch 6][Batch 3899], Speed: 5.637 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.820 +[Epoch 6][Batch 3999], Speed: 5.457 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.820 +[Epoch 6][Batch 4099], Speed: 5.848 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.820 +[Epoch 6][Batch 4199], Speed: 5.937 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.820 +[Epoch 6][Batch 4299], Speed: 5.978 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.820 +[Epoch 6][Batch 4399], Speed: 5.383 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.820 +[Epoch 6][Batch 4499], Speed: 5.981 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.820 +[Epoch 6][Batch 4599], Speed: 5.631 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.819 +[Epoch 6][Batch 4699], Speed: 5.940 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.819 +[Epoch 6][Batch 4799], Speed: 5.549 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.819 +[Epoch 6][Batch 4899], Speed: 5.881 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.819 +[Epoch 6][Batch 4999], Speed: 5.465 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.819 +[Epoch 6][Batch 5099], Speed: 5.824 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.931,RCNNL1Loss=0.819 +[Epoch 6][Batch 5199], Speed: 6.060 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.932,RCNNL1Loss=0.819 +[Epoch 6][Batch 5299], Speed: 5.644 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.932,RCNNL1Loss=0.818 +[Epoch 6][Batch 5399], Speed: 5.796 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.932,RCNNL1Loss=0.818 +[Epoch 6][Batch 5499], Speed: 5.864 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.932,RCNNL1Loss=0.818 +[Epoch 6][Batch 5599], Speed: 5.918 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.932,RCNNL1Loss=0.818 +[Epoch 6][Batch 5699], Speed: 6.083 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.932,RCNNL1Loss=0.818 +[Epoch 6][Batch 5799], Speed: 6.279 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.269,RCNNAcc=0.932,RCNNL1Loss=0.818 +[Epoch 6][Batch 5899], Speed: 5.856 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.818 +[Epoch 6][Batch 5999], Speed: 5.398 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.817 +[Epoch 6][Batch 6099], Speed: 5.704 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.817 +[Epoch 6][Batch 6199], Speed: 6.126 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.986,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.817 +[Epoch 6][Batch 6299], Speed: 6.036 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.817 +[Epoch 6][Batch 6399], Speed: 5.837 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.817 +[Epoch 6][Batch 6499], Speed: 6.229 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.817 +[Epoch 6][Batch 6599], Speed: 6.091 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.230,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.817 +[Epoch 6][Batch 6699], Speed: 6.256 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.816 +[Epoch 6][Batch 6799], Speed: 5.650 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.816 +[Epoch 6][Batch 6899], Speed: 5.879 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.816 +[Epoch 6][Batch 6999], Speed: 6.093 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.816 +[Epoch 6][Batch 7099], Speed: 5.761 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.816 +[Epoch 6][Batch 7199], Speed: 5.549 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.816 +[Epoch 6][Batch 7299], Speed: 5.665 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.816 +[Epoch 6][Batch 7399], Speed: 5.871 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.815 +[Epoch 6][Batch 7499], Speed: 5.868 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.815 +[Epoch 6][Batch 7599], Speed: 5.861 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.815 +[Epoch 6][Batch 7699], Speed: 5.950 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.815 +[Epoch 6][Batch 7799], Speed: 5.756 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.815 +[Epoch 6][Batch 7899], Speed: 6.498 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.815 +[Epoch 6][Batch 7999], Speed: 6.002 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.815 +[Epoch 6][Batch 8099], Speed: 5.814 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.814 +[Epoch 6][Batch 8199], Speed: 6.462 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.814 +[Epoch 6][Batch 8299], Speed: 5.446 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.268,RCNNAcc=0.932,RCNNL1Loss=0.814 +[Epoch 6][Batch 8399], Speed: 5.951 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.814 +[Epoch 6][Batch 8499], Speed: 6.291 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.814 +[Epoch 6][Batch 8599], Speed: 5.679 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.814 +[Epoch 6][Batch 8699], Speed: 6.228 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.814 +[Epoch 6][Batch 8799], Speed: 6.057 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.813 +[Epoch 6][Batch 8899], Speed: 6.321 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.813 +[Epoch 6][Batch 8999], Speed: 5.658 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.813 +[Epoch 6][Batch 9099], Speed: 6.248 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.813 +[Epoch 6][Batch 9199], Speed: 6.025 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.813 +[Epoch 6][Batch 9299], Speed: 5.883 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.813 +[Epoch 6][Batch 9399], Speed: 5.944 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.813 +[Epoch 6][Batch 9499], Speed: 5.550 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.813 +[Epoch 6][Batch 9599], Speed: 5.987 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.812 +[Epoch 6][Batch 9699], Speed: 5.648 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.812 +[Epoch 6][Batch 9799], Speed: 5.975 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.812 +[Epoch 6][Batch 9899], Speed: 5.924 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.812 +[Epoch 6][Batch 9999], Speed: 5.891 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.812 +[Epoch 6][Batch 10099], Speed: 6.323 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.812 +[Epoch 6][Batch 10199], Speed: 6.018 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.812 +[Epoch 6][Batch 10299], Speed: 5.749 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.812 +[Epoch 6][Batch 10399], Speed: 5.768 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.811 +[Epoch 6][Batch 10499], Speed: 5.709 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.811 +[Epoch 6][Batch 10599], Speed: 6.068 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.811 +[Epoch 6][Batch 10699], Speed: 5.600 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.811 +[Epoch 6][Batch 10799], Speed: 6.032 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.811 +[Epoch 6][Batch 10899], Speed: 6.214 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.811 +[Epoch 6][Batch 10999], Speed: 6.245 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.267,RCNNAcc=0.932,RCNNL1Loss=0.811 +[Epoch 6][Batch 11099], Speed: 5.741 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.811 +[Epoch 6][Batch 11199], Speed: 5.852 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 11299], Speed: 6.317 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 11399], Speed: 5.357 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 11499], Speed: 6.061 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 11599], Speed: 5.928 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 11699], Speed: 5.969 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 11799], Speed: 6.001 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 11899], Speed: 6.004 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 11999], Speed: 5.629 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.810 +[Epoch 6][Batch 12099], Speed: 6.167 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.809 +[Epoch 6][Batch 12199], Speed: 6.168 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.809 +[Epoch 6][Batch 12299], Speed: 5.784 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.809 +[Epoch 6][Batch 12399], Speed: 6.004 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.809 +[Epoch 6][Batch 12499], Speed: 6.271 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.809 +[Epoch 6][Batch 12599], Speed: 5.961 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.173,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.809 +[Epoch 6][Batch 12699], Speed: 5.767 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.809 +[Epoch 6][Batch 12799], Speed: 5.868 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.809 +[Epoch 6][Batch 12899], Speed: 5.977 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 12999], Speed: 5.898 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 13099], Speed: 5.540 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 13199], Speed: 5.420 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 13299], Speed: 5.731 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 13399], Speed: 5.830 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 13499], Speed: 6.165 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 13599], Speed: 6.123 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 13699], Speed: 6.372 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.808 +[Epoch 6][Batch 13799], Speed: 6.126 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.266,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6][Batch 13899], Speed: 6.168 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6][Batch 13999], Speed: 6.131 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6][Batch 14099], Speed: 6.103 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6][Batch 14199], Speed: 5.829 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6][Batch 14299], Speed: 5.776 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6][Batch 14399], Speed: 6.068 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6][Batch 14499], Speed: 5.752 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6][Batch 14599], Speed: 5.361 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.807 +[Epoch 6] Training cost: 19852.598, RPN_Conf=0.029,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.174,RCNN_SmoothL1=0.229 +[Epoch 6] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.586 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.405 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.226 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.409 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.476 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.309 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.506 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.537 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.359 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.575 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.653 +person=52.6 +bicycle=30.8 +car=43.1 +motorcycle=42.1 +airplane=54.4 +bus=58.8 +train=57.6 +truck=28.7 +boat=22.8 +traffic light=27.1 +fire hydrant=66.3 +stop sign=60.2 +parking meter=40.9 +bench=23.3 +bird=33.5 +cat=61.7 +dog=53.4 +horse=40.9 +sheep=45.5 +cow=49.6 +elephant=46.9 +bear=66.1 +zebra=58.7 +giraffe=64.9 +backpack=13.0 +umbrella=35.4 +handbag=11.6 +tie=31.1 +suitcase=32.0 +frisbee=65.2 +skis=18.5 +snowboard=33.3 +sports ball=40.5 +kite=35.2 +baseball bat=30.7 +baseball glove=37.6 +skateboard=40.0 +surfboard=32.6 +tennis racket=47.8 +bottle=39.0 +wine glass=33.5 +cup=40.8 +fork=32.8 +knife=17.6 +spoon=14.9 +bowl=38.7 +banana=23.8 +apple=16.4 +sandwich=28.1 +orange=25.3 +broccoli=21.3 +carrot=17.4 +hot dog=18.5 +pizza=47.1 +donut=46.9 +cake=35.3 +chair=27.4 +couch=37.0 +potted plant=25.2 +bed=31.8 +dining table=22.5 +toilet=54.3 +tv=51.1 +laptop=52.7 +mouse=59.4 +remote=31.1 +keyboard=48.4 +cell phone=31.9 +microwave=52.9 +oven=29.7 +toaster=22.4 +sink=32.3 +refrigerator=48.2 +book=17.3 +clock=45.8 +vase=36.5 +scissors=33.1 +teddy bear=41.6 +hair drier=0.0 +toothbrush=20.2 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.3 +[Epoch 6] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0006_37.3000.params +[Epoch 7][Batch 99], Speed: 6.225 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.234,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.806 +[Epoch 7][Batch 199], Speed: 6.680 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.232,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.806 +[Epoch 7][Batch 299], Speed: 6.347 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.232,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.806 +[Epoch 7][Batch 399], Speed: 5.925 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.232,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.806 +[Epoch 7][Batch 499], Speed: 6.372 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.045,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.229,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.806 +[Epoch 7][Batch 599], Speed: 6.046 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.228,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.806 +[Epoch 7][Batch 699], Speed: 5.919 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.806 +[Epoch 7][Batch 799], Speed: 5.858 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.805 +[Epoch 7][Batch 899], Speed: 5.808 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.805 +[Epoch 7][Batch 999], Speed: 5.688 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.805 +[Epoch 7][Batch 1099], Speed: 6.127 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.805 +[Epoch 7][Batch 1199], Speed: 6.084 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.805 +[Epoch 7][Batch 1299], Speed: 6.056 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.805 +[Epoch 7][Batch 1399], Speed: 5.511 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.805 +[Epoch 7][Batch 1499], Speed: 5.779 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.804 +[Epoch 7][Batch 1599], Speed: 6.104 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.804 +[Epoch 7][Batch 1699], Speed: 5.748 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.804 +[Epoch 7][Batch 1799], Speed: 5.658 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.265,RCNNAcc=0.932,RCNNL1Loss=0.804 +[Epoch 7][Batch 1899], Speed: 5.788 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.932,RCNNL1Loss=0.804 +[Epoch 7][Batch 1999], Speed: 5.825 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.932,RCNNL1Loss=0.804 +[Epoch 7][Batch 2099], Speed: 5.641 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.932,RCNNL1Loss=0.804 +[Epoch 7][Batch 2199], Speed: 5.990 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.932,RCNNL1Loss=0.804 +[Epoch 7][Batch 2299], Speed: 6.134 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.803 +[Epoch 7][Batch 2399], Speed: 5.716 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.803 +[Epoch 7][Batch 2499], Speed: 5.876 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.803 +[Epoch 7][Batch 2599], Speed: 6.170 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.803 +[Epoch 7][Batch 2699], Speed: 5.938 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.803 +[Epoch 7][Batch 2799], Speed: 5.639 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.803 +[Epoch 7][Batch 2899], Speed: 6.032 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.803 +[Epoch 7][Batch 2999], Speed: 6.030 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.802 +[Epoch 7][Batch 3099], Speed: 6.222 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.802 +[Epoch 7][Batch 3199], Speed: 6.042 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.802 +[Epoch 7][Batch 3299], Speed: 5.990 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.802 +[Epoch 7][Batch 3399], Speed: 5.591 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.802 +[Epoch 7][Batch 3499], Speed: 6.156 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.802 +[Epoch 7][Batch 3599], Speed: 5.843 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.802 +[Epoch 7][Batch 3699], Speed: 6.094 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.802 +[Epoch 7][Batch 3799], Speed: 5.969 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 3899], Speed: 5.848 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 3999], Speed: 6.019 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 4099], Speed: 5.890 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 4199], Speed: 5.625 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 4299], Speed: 6.225 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 4399], Speed: 5.757 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.264,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 4499], Speed: 5.578 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 4599], Speed: 6.328 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.801 +[Epoch 7][Batch 4699], Speed: 6.228 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 4799], Speed: 5.743 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 4899], Speed: 5.635 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 4999], Speed: 5.698 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 5099], Speed: 6.099 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 5199], Speed: 5.157 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 5299], Speed: 6.147 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 5399], Speed: 6.384 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 5499], Speed: 5.804 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.800 +[Epoch 7][Batch 5599], Speed: 5.642 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 5699], Speed: 5.994 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 5799], Speed: 5.703 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 5899], Speed: 6.096 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 5999], Speed: 6.318 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 6099], Speed: 5.887 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 6199], Speed: 5.958 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 6299], Speed: 5.747 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 6399], Speed: 5.954 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.799 +[Epoch 7][Batch 6499], Speed: 5.743 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 6599], Speed: 6.307 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 6699], Speed: 5.491 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 6799], Speed: 5.695 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 6899], Speed: 5.865 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 6999], Speed: 5.969 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 7099], Speed: 5.641 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 7199], Speed: 5.337 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.263,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 7299], Speed: 6.126 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.798 +[Epoch 7][Batch 7399], Speed: 5.928 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 7499], Speed: 5.712 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 7599], Speed: 6.208 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 7699], Speed: 5.808 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 7799], Speed: 5.319 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 7899], Speed: 5.919 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 7999], Speed: 5.821 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 8099], Speed: 6.095 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 8199], Speed: 5.753 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.797 +[Epoch 7][Batch 8299], Speed: 5.811 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 8399], Speed: 6.257 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 8499], Speed: 5.483 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 8599], Speed: 6.074 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 8699], Speed: 5.466 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 8799], Speed: 6.336 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 8899], Speed: 6.187 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 8999], Speed: 6.649 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 9099], Speed: 6.278 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.796 +[Epoch 7][Batch 9199], Speed: 5.826 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 9299], Speed: 5.957 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 9399], Speed: 6.451 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 9499], Speed: 6.090 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 9599], Speed: 5.757 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 9699], Speed: 5.518 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 9799], Speed: 5.816 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 9899], Speed: 6.051 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 9999], Speed: 5.531 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 10099], Speed: 5.782 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.795 +[Epoch 7][Batch 10199], Speed: 5.652 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 10299], Speed: 6.327 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 10399], Speed: 5.769 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.262,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 10499], Speed: 5.924 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 10599], Speed: 5.944 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 10699], Speed: 5.720 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 10799], Speed: 5.913 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 10899], Speed: 6.306 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 10999], Speed: 5.581 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.794 +[Epoch 7][Batch 11099], Speed: 5.512 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11199], Speed: 6.130 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11299], Speed: 6.015 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11399], Speed: 5.842 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11499], Speed: 5.847 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11599], Speed: 5.778 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11699], Speed: 6.618 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11799], Speed: 5.573 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11899], Speed: 6.488 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 11999], Speed: 6.300 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.793 +[Epoch 7][Batch 12099], Speed: 6.289 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12199], Speed: 5.672 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12299], Speed: 5.917 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12399], Speed: 5.672 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12499], Speed: 5.971 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12599], Speed: 5.748 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12699], Speed: 5.513 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12799], Speed: 5.802 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12899], Speed: 5.687 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 12999], Speed: 5.707 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 13099], Speed: 6.111 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.792 +[Epoch 7][Batch 13199], Speed: 5.905 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 13299], Speed: 5.938 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 13399], Speed: 6.087 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 13499], Speed: 5.776 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 13599], Speed: 6.109 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 13699], Speed: 6.284 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 13799], Speed: 5.715 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 13899], Speed: 5.778 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.171,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.261,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 13999], Speed: 5.626 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 14099], Speed: 5.392 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.791 +[Epoch 7][Batch 14199], Speed: 6.155 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 7][Batch 14299], Speed: 6.043 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 7][Batch 14399], Speed: 5.606 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 7][Batch 14499], Speed: 5.362 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 7][Batch 14599], Speed: 5.729 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.226,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 7] Training cost: 19889.446, RPN_Conf=0.028,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.172,RCNN_SmoothL1=0.226 +[Epoch 7] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.376 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.591 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.410 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.234 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.420 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.473 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.316 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.510 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.540 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.370 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.584 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.652 +person=52.8 +bicycle=26.8 +car=40.3 +motorcycle=42.4 +airplane=54.6 +bus=59.1 +train=60.2 +truck=33.8 +boat=24.2 +traffic light=26.3 +fire hydrant=61.3 +stop sign=57.8 +parking meter=35.9 +bench=22.6 +bird=35.8 +cat=61.3 +dog=51.7 +horse=54.8 +sheep=47.0 +cow=52.0 +elephant=59.1 +bear=52.4 +zebra=57.3 +giraffe=63.3 +backpack=15.3 +umbrella=34.4 +handbag=14.8 +tie=31.9 +suitcase=36.2 +frisbee=62.4 +skis=21.8 +snowboard=31.1 +sports ball=43.4 +kite=41.7 +baseball bat=30.0 +baseball glove=37.4 +skateboard=49.5 +surfboard=34.0 +tennis racket=45.9 +bottle=40.1 +wine glass=35.8 +cup=40.9 +fork=31.5 +knife=19.4 +spoon=14.7 +bowl=39.5 +banana=24.4 +apple=16.9 +sandwich=32.8 +orange=20.2 +broccoli=20.3 +carrot=16.3 +hot dog=30.0 +pizza=47.0 +donut=38.2 +cake=33.4 +chair=24.7 +couch=35.1 +potted plant=25.4 +bed=36.1 +dining table=24.1 +toilet=55.2 +tv=51.4 +laptop=55.9 +mouse=55.6 +remote=32.7 +keyboard=44.8 +cell phone=33.9 +microwave=54.2 +oven=29.0 +toaster=24.4 +sink=33.7 +refrigerator=48.6 +book=13.1 +clock=45.2 +vase=36.3 +scissors=23.7 +teddy bear=39.8 +hair drier=4.0 +toothbrush=18.9 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.6 +[Epoch 7] mAP 37.6 higher than current best [37.5] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 7] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0007_37.6000.params +[Epoch 8][Batch 99], Speed: 6.424 samples/sec, RPN_Conf=0.029,RPN_SmoothL1=0.046,RCNN_CrossEntropy=0.177,RCNN_SmoothL1=0.235,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 8][Batch 199], Speed: 6.258 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.225,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 8][Batch 299], Speed: 6.122 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 8][Batch 399], Speed: 6.259 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.790 +[Epoch 8][Batch 499], Speed: 6.695 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.789 +[Epoch 8][Batch 599], Speed: 6.734 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.789 +[Epoch 8][Batch 699], Speed: 6.214 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.222,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.789 +[Epoch 8][Batch 799], Speed: 6.124 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.789 +[Epoch 8][Batch 899], Speed: 6.339 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.222,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.789 +[Epoch 8][Batch 999], Speed: 5.843 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.222,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.789 +[Epoch 8][Batch 1099], Speed: 5.731 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.789 +[Epoch 8][Batch 1199], Speed: 5.992 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.789 +[Epoch 8][Batch 1299], Speed: 5.992 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.788 +[Epoch 8][Batch 1399], Speed: 6.633 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.788 +[Epoch 8][Batch 1499], Speed: 6.337 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.788 +[Epoch 8][Batch 1599], Speed: 6.856 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.222,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.788 +[Epoch 8][Batch 1699], Speed: 5.570 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.788 +[Epoch 8][Batch 1799], Speed: 5.783 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.788 +[Epoch 8][Batch 1899], Speed: 5.689 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.933,RCNNL1Loss=0.788 +[Epoch 8][Batch 1999], Speed: 6.001 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.934,RCNNL1Loss=0.788 +[Epoch 8][Batch 2099], Speed: 6.052 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.934,RCNNL1Loss=0.788 +[Epoch 8][Batch 2199], Speed: 6.592 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 2299], Speed: 6.215 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 2399], Speed: 6.430 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 2499], Speed: 5.638 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.260,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 2599], Speed: 6.213 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 2699], Speed: 6.356 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 2799], Speed: 6.445 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.221,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 2899], Speed: 5.398 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.222,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 2999], Speed: 5.752 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.222,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 3099], Speed: 5.875 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.222,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.787 +[Epoch 8][Batch 3199], Speed: 6.228 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 3299], Speed: 6.296 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 3399], Speed: 6.157 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 3499], Speed: 5.722 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 3599], Speed: 5.890 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 3699], Speed: 5.741 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 3799], Speed: 5.653 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 3899], Speed: 5.912 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 3999], Speed: 5.677 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.786 +[Epoch 8][Batch 4099], Speed: 5.775 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4199], Speed: 5.705 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4299], Speed: 6.030 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4399], Speed: 5.583 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4499], Speed: 5.618 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4599], Speed: 6.634 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4699], Speed: 5.581 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4799], Speed: 5.718 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4899], Speed: 5.774 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 4999], Speed: 5.526 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 5099], Speed: 5.638 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.785 +[Epoch 8][Batch 5199], Speed: 5.888 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 5299], Speed: 6.068 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 5399], Speed: 5.548 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 5499], Speed: 6.028 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 5599], Speed: 5.785 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 5699], Speed: 6.187 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 5799], Speed: 5.951 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.259,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 5899], Speed: 5.906 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 5999], Speed: 5.758 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 6099], Speed: 5.905 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.784 +[Epoch 8][Batch 6199], Speed: 6.100 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 6299], Speed: 5.706 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.168,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 6399], Speed: 5.945 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 6499], Speed: 6.179 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 6599], Speed: 5.243 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 6699], Speed: 5.632 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 6799], Speed: 6.091 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 6899], Speed: 5.893 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 6999], Speed: 6.042 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 7099], Speed: 6.309 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 7199], Speed: 5.753 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.783 +[Epoch 8][Batch 7299], Speed: 5.864 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 7399], Speed: 6.059 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 7499], Speed: 5.767 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 7599], Speed: 6.068 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 7699], Speed: 6.068 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 7799], Speed: 5.979 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 7899], Speed: 5.599 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 7999], Speed: 5.544 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 8099], Speed: 6.064 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 8199], Speed: 5.488 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 8299], Speed: 6.181 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.782 +[Epoch 8][Batch 8399], Speed: 6.136 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 8499], Speed: 5.936 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 8599], Speed: 6.164 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 8699], Speed: 5.487 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 8799], Speed: 5.952 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 8899], Speed: 5.880 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 8999], Speed: 6.000 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 9099], Speed: 6.135 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 9199], Speed: 6.058 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 9299], Speed: 5.809 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.258,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 9399], Speed: 6.092 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.781 +[Epoch 8][Batch 9499], Speed: 5.506 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 9599], Speed: 5.934 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 9699], Speed: 5.635 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 9799], Speed: 6.214 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 9899], Speed: 6.084 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 9999], Speed: 6.208 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 10099], Speed: 5.790 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 10199], Speed: 5.604 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 10299], Speed: 5.852 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 10399], Speed: 6.180 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.169,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 10499], Speed: 6.183 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.780 +[Epoch 8][Batch 10599], Speed: 6.079 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 10699], Speed: 5.869 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 10799], Speed: 5.633 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 10899], Speed: 6.010 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 10999], Speed: 6.393 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 11099], Speed: 5.848 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 11199], Speed: 6.087 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 11299], Speed: 5.355 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 11399], Speed: 6.154 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 11499], Speed: 6.028 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 11599], Speed: 5.938 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 11699], Speed: 5.885 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.779 +[Epoch 8][Batch 11799], Speed: 5.713 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 11899], Speed: 6.229 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 11999], Speed: 5.686 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.224,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12099], Speed: 5.347 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12199], Speed: 6.289 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12299], Speed: 6.205 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12399], Speed: 5.465 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12499], Speed: 6.230 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12599], Speed: 6.282 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12699], Speed: 5.702 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12799], Speed: 5.780 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12899], Speed: 5.313 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.778 +[Epoch 8][Batch 12999], Speed: 5.853 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13099], Speed: 5.468 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13199], Speed: 5.835 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.257,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13299], Speed: 6.265 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13399], Speed: 6.085 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13499], Speed: 6.132 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13599], Speed: 5.925 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13699], Speed: 6.001 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13799], Speed: 5.696 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13899], Speed: 6.154 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 13999], Speed: 6.234 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 14099], Speed: 6.472 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.777 +[Epoch 8][Batch 14199], Speed: 5.633 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 8][Batch 14299], Speed: 6.018 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 8][Batch 14399], Speed: 5.810 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 8][Batch 14499], Speed: 5.848 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 8][Batch 14599], Speed: 6.067 samples/sec, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 8] Training cost: 19745.254, RPN_Conf=0.028,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.170,RCNN_SmoothL1=0.223 +[Epoch 8] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.381 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.591 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.415 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.244 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.420 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.482 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.315 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.513 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.544 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.382 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.583 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.654 +person=52.3 +bicycle=28.2 +car=42.1 +motorcycle=42.1 +airplane=58.2 +bus=60.0 +train=58.0 +truck=30.8 +boat=24.5 +traffic light=21.6 +fire hydrant=61.5 +stop sign=60.3 +parking meter=47.5 +bench=22.7 +bird=32.5 +cat=61.9 +dog=53.2 +horse=49.4 +sheep=47.4 +cow=54.7 +elephant=58.7 +bear=61.0 +zebra=60.0 +giraffe=57.9 +backpack=12.9 +umbrella=36.4 +handbag=15.5 +tie=31.5 +suitcase=35.7 +frisbee=65.1 +skis=21.9 +snowboard=42.5 +sports ball=40.2 +kite=39.3 +baseball bat=29.0 +baseball glove=35.9 +skateboard=48.8 +surfboard=37.1 +tennis racket=45.1 +bottle=38.4 +wine glass=33.8 +cup=42.8 +fork=32.6 +knife=18.8 +spoon=17.8 +bowl=37.3 +banana=24.0 +apple=12.8 +sandwich=30.7 +orange=22.0 +broccoli=18.4 +carrot=19.6 +hot dog=24.1 +pizza=49.4 +donut=47.7 +cake=30.6 +chair=26.5 +couch=37.8 +potted plant=26.0 +bed=33.8 +dining table=23.3 +toilet=55.6 +tv=53.0 +laptop=57.2 +mouse=56.9 +remote=30.7 +keyboard=46.1 +cell phone=32.7 +microwave=53.7 +oven=31.3 +toaster=34.0 +sink=35.2 +refrigerator=50.8 +book=14.0 +clock=48.1 +vase=29.6 +scissors=20.1 +teddy bear=41.5 +hair drier=1.7 +toothbrush=21.3 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=38.1 +[Epoch 8] mAP 38.1 higher than current best [37.6] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 8] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0008_38.1000.params +[Epoch 9][Batch 99], Speed: 6.452 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 9][Batch 199], Speed: 6.642 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.217,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 9][Batch 299], Speed: 5.469 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 9][Batch 399], Speed: 5.829 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.218,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 9][Batch 499], Speed: 6.094 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.776 +[Epoch 9][Batch 599], Speed: 5.595 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 699], Speed: 6.201 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 799], Speed: 5.730 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 899], Speed: 6.044 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 999], Speed: 6.825 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 1099], Speed: 6.490 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 1199], Speed: 6.250 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 1299], Speed: 5.497 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 1399], Speed: 5.948 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.217,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 1499], Speed: 6.260 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 1599], Speed: 6.280 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.218,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.775 +[Epoch 9][Batch 1699], Speed: 5.924 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.218,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 1799], Speed: 5.942 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 1899], Speed: 6.313 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.218,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 1999], Speed: 5.303 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.218,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 2099], Speed: 5.790 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.256,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 2199], Speed: 5.948 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 2299], Speed: 5.755 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 2399], Speed: 6.009 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 2499], Speed: 6.133 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 2599], Speed: 6.046 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 2699], Speed: 6.374 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.774 +[Epoch 9][Batch 2799], Speed: 5.118 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 2899], Speed: 6.054 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 2999], Speed: 5.732 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3099], Speed: 6.219 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3199], Speed: 5.995 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3299], Speed: 6.116 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3399], Speed: 5.693 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3499], Speed: 6.178 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3599], Speed: 5.866 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3699], Speed: 5.830 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3799], Speed: 6.110 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.219,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.773 +[Epoch 9][Batch 3899], Speed: 5.931 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.934,RCNNL1Loss=0.772 +[Epoch 9][Batch 3999], Speed: 5.886 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4099], Speed: 5.601 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4199], Speed: 5.689 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4299], Speed: 6.614 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4399], Speed: 5.572 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4499], Speed: 5.850 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4599], Speed: 5.992 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4699], Speed: 6.054 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4799], Speed: 5.582 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4899], Speed: 5.669 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.772 +[Epoch 9][Batch 4999], Speed: 6.319 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5099], Speed: 5.730 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5199], Speed: 6.277 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.987,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5299], Speed: 6.246 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5399], Speed: 5.572 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5499], Speed: 5.778 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5599], Speed: 5.819 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5699], Speed: 6.160 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5799], Speed: 5.945 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5899], Speed: 5.713 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 5999], Speed: 5.548 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.255,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 6099], Speed: 5.919 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.771 +[Epoch 9][Batch 6199], Speed: 5.227 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 6299], Speed: 6.120 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 6399], Speed: 5.290 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 6499], Speed: 5.531 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 6599], Speed: 6.511 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 6699], Speed: 5.628 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 6799], Speed: 6.190 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 6899], Speed: 6.332 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 6999], Speed: 5.842 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 7099], Speed: 5.883 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 7199], Speed: 5.642 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 7299], Speed: 5.839 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.770 +[Epoch 9][Batch 7399], Speed: 5.798 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 7499], Speed: 6.107 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 7599], Speed: 5.690 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 7699], Speed: 5.842 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 7799], Speed: 5.355 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 7899], Speed: 5.864 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 7999], Speed: 6.089 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 8099], Speed: 5.950 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 8199], Speed: 5.971 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 8299], Speed: 5.842 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 8399], Speed: 5.634 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 8499], Speed: 5.934 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 8599], Speed: 6.108 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.769 +[Epoch 9][Batch 8699], Speed: 5.844 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 8799], Speed: 5.839 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 8899], Speed: 6.457 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 8999], Speed: 4.955 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9099], Speed: 5.818 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9199], Speed: 5.741 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9299], Speed: 5.614 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9399], Speed: 6.047 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9499], Speed: 5.890 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9599], Speed: 5.435 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9699], Speed: 5.803 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9799], Speed: 5.604 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9899], Speed: 5.774 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.219,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.768 +[Epoch 9][Batch 9999], Speed: 6.275 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.219,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10099], Speed: 5.370 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10199], Speed: 6.136 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10299], Speed: 6.544 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10399], Speed: 5.638 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.254,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10499], Speed: 6.144 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10599], Speed: 5.533 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10699], Speed: 5.860 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10799], Speed: 6.171 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.219,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10899], Speed: 5.897 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.219,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 10999], Speed: 6.085 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.219,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 11099], Speed: 6.264 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 11199], Speed: 5.333 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 11299], Speed: 6.290 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.767 +[Epoch 9][Batch 11399], Speed: 5.891 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 11499], Speed: 6.303 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 11599], Speed: 5.791 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 11699], Speed: 5.419 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 11799], Speed: 6.447 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 11899], Speed: 5.441 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 11999], Speed: 6.381 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12099], Speed: 5.564 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12199], Speed: 5.784 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12299], Speed: 5.951 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12399], Speed: 6.147 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12499], Speed: 6.225 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12599], Speed: 5.974 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12699], Speed: 5.620 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12799], Speed: 6.210 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.766 +[Epoch 9][Batch 12899], Speed: 5.935 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 12999], Speed: 5.819 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13099], Speed: 5.867 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13199], Speed: 5.735 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13299], Speed: 5.713 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13399], Speed: 5.836 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13499], Speed: 5.909 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13599], Speed: 6.053 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13699], Speed: 5.902 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13799], Speed: 5.901 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13899], Speed: 5.703 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 13999], Speed: 5.927 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 14099], Speed: 5.922 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 14199], Speed: 5.930 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.765 +[Epoch 9][Batch 14299], Speed: 5.662 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 9][Batch 14399], Speed: 5.614 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 9][Batch 14499], Speed: 5.939 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 9][Batch 14599], Speed: 6.494 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 9] Training cost: 19904.499, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.167,RCNN_SmoothL1=0.220 +[Epoch 9] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.373 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.583 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.406 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.244 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.421 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.477 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.313 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.508 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.537 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.354 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.582 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.667 +person=53.0 +bicycle=26.1 +car=42.1 +motorcycle=40.0 +airplane=60.4 +bus=60.2 +train=55.6 +truck=29.4 +boat=22.9 +traffic light=25.3 +fire hydrant=62.8 +stop sign=59.7 +parking meter=42.2 +bench=22.9 +bird=33.6 +cat=60.8 +dog=51.2 +horse=53.1 +sheep=46.2 +cow=49.9 +elephant=53.3 +bear=54.6 +zebra=55.2 +giraffe=60.1 +backpack=13.7 +umbrella=35.5 +handbag=13.8 +tie=32.7 +suitcase=29.8 +frisbee=62.8 +skis=22.2 +snowboard=31.9 +sports ball=40.4 +kite=34.1 +baseball bat=27.6 +baseball glove=36.6 +skateboard=51.4 +surfboard=35.8 +tennis racket=45.8 +bottle=39.4 +wine glass=32.9 +cup=41.7 +fork=34.5 +knife=17.7 +spoon=15.0 +bowl=35.8 +banana=22.4 +apple=14.0 +sandwich=23.3 +orange=26.7 +broccoli=16.6 +carrot=15.5 +hot dog=32.9 +pizza=46.4 +donut=40.1 +cake=32.3 +chair=25.3 +couch=37.4 +potted plant=24.8 +bed=30.7 +dining table=22.3 +toilet=49.6 +tv=50.2 +laptop=56.5 +mouse=57.3 +remote=30.0 +keyboard=49.8 +cell phone=31.5 +microwave=55.1 +oven=33.6 +toaster=29.5 +sink=35.4 +refrigerator=48.7 +book=13.9 +clock=45.9 +vase=36.1 +scissors=27.4 +teddy bear=38.7 +hair drier=7.7 +toothbrush=24.1 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.3 +[Epoch 9] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0009_37.3000.params +[Epoch 10][Batch 99], Speed: 6.371 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 10][Batch 199], Speed: 6.810 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 10][Batch 299], Speed: 5.911 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 10][Batch 399], Speed: 5.990 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 10][Batch 499], Speed: 6.137 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.253,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 10][Batch 599], Speed: 5.882 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 10][Batch 699], Speed: 6.342 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 10][Batch 799], Speed: 5.845 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.764 +[Epoch 10][Batch 899], Speed: 6.036 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 999], Speed: 6.074 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1099], Speed: 6.161 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1199], Speed: 5.871 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1299], Speed: 5.883 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1399], Speed: 6.089 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1499], Speed: 5.606 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1599], Speed: 5.341 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1699], Speed: 5.758 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1799], Speed: 5.790 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1899], Speed: 5.669 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 1999], Speed: 6.077 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.763 +[Epoch 10][Batch 2099], Speed: 5.953 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2199], Speed: 5.646 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2299], Speed: 5.911 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2399], Speed: 6.193 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2499], Speed: 5.505 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2599], Speed: 6.223 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2699], Speed: 5.580 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2799], Speed: 6.305 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2899], Speed: 5.629 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 2999], Speed: 6.202 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 3099], Speed: 6.038 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 3199], Speed: 6.346 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 3299], Speed: 5.537 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.762 +[Epoch 10][Batch 3399], Speed: 6.618 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 3499], Speed: 5.944 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 3599], Speed: 5.532 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 3699], Speed: 6.289 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 3799], Speed: 5.409 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 3899], Speed: 5.625 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 3999], Speed: 6.165 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 4099], Speed: 5.544 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 4199], Speed: 5.772 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 4299], Speed: 6.042 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 4399], Speed: 5.585 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 4499], Speed: 6.532 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 4599], Speed: 5.436 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.761 +[Epoch 10][Batch 4699], Speed: 5.706 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 4799], Speed: 5.944 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.252,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 4899], Speed: 5.479 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 4999], Speed: 5.969 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5099], Speed: 6.161 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5199], Speed: 5.646 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5299], Speed: 5.818 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5399], Speed: 6.028 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5499], Speed: 5.542 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5599], Speed: 6.010 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5699], Speed: 6.600 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5799], Speed: 5.533 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5899], Speed: 6.470 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 5999], Speed: 6.068 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.760 +[Epoch 10][Batch 6099], Speed: 5.829 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6199], Speed: 5.705 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6299], Speed: 6.391 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6399], Speed: 5.936 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6499], Speed: 5.909 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6599], Speed: 6.208 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6699], Speed: 5.835 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6799], Speed: 5.881 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6899], Speed: 6.356 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 6999], Speed: 6.291 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 7099], Speed: 5.546 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 7199], Speed: 5.644 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 7299], Speed: 6.225 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 7399], Speed: 5.668 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.759 +[Epoch 10][Batch 7499], Speed: 6.122 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 7599], Speed: 5.775 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 7699], Speed: 6.053 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 7799], Speed: 6.444 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 7899], Speed: 5.955 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 7999], Speed: 5.981 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8099], Speed: 6.508 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8199], Speed: 6.365 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8299], Speed: 5.950 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8399], Speed: 5.964 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8499], Speed: 5.925 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8599], Speed: 5.913 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8699], Speed: 5.807 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8799], Speed: 6.255 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8899], Speed: 5.732 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.935,RCNNL1Loss=0.758 +[Epoch 10][Batch 8999], Speed: 5.671 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9099], Speed: 5.861 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9199], Speed: 5.468 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9299], Speed: 5.619 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9399], Speed: 5.465 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9499], Speed: 5.427 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.251,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9599], Speed: 5.845 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9699], Speed: 6.291 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9799], Speed: 5.728 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9899], Speed: 5.679 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 9999], Speed: 5.954 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 10099], Speed: 6.128 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 10199], Speed: 5.651 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 10299], Speed: 5.961 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 10399], Speed: 5.542 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 10499], Speed: 5.723 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.757 +[Epoch 10][Batch 10599], Speed: 5.944 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 10699], Speed: 5.797 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 10799], Speed: 6.037 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 10899], Speed: 6.184 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 10999], Speed: 5.808 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11099], Speed: 5.347 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11199], Speed: 6.329 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11299], Speed: 5.728 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11399], Speed: 5.712 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11499], Speed: 6.460 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11599], Speed: 5.469 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11699], Speed: 6.325 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11799], Speed: 6.061 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11899], Speed: 5.942 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 11999], Speed: 5.624 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 12099], Speed: 5.597 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 12199], Speed: 5.793 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.756 +[Epoch 10][Batch 12299], Speed: 5.728 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 12399], Speed: 6.089 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 12499], Speed: 5.849 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 12599], Speed: 6.142 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 12699], Speed: 5.985 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 12799], Speed: 5.470 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 12899], Speed: 5.488 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 12999], Speed: 5.429 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13099], Speed: 5.681 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13199], Speed: 6.161 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13299], Speed: 6.185 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13399], Speed: 6.162 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13499], Speed: 5.972 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13599], Speed: 6.286 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13699], Speed: 6.425 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13799], Speed: 5.824 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.755 +[Epoch 10][Batch 13899], Speed: 5.953 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 10][Batch 13999], Speed: 6.106 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 10][Batch 14099], Speed: 5.856 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 10][Batch 14199], Speed: 5.482 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 10][Batch 14299], Speed: 5.736 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 10][Batch 14399], Speed: 5.794 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 10][Batch 14499], Speed: 5.328 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 10][Batch 14599], Speed: 5.326 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 10] Training cost: 19891.029, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.166,RCNN_SmoothL1=0.218 +[Epoch 10] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.379 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.589 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.411 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.246 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.421 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.476 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.316 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.517 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.551 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.389 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.593 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.651 +person=53.5 +bicycle=29.9 +car=42.0 +motorcycle=40.3 +airplane=61.7 +bus=58.7 +train=57.2 +truck=31.7 +boat=24.0 +traffic light=25.1 +fire hydrant=64.0 +stop sign=62.5 +parking meter=45.8 +bench=20.2 +bird=32.5 +cat=58.5 +dog=56.1 +horse=52.0 +sheep=46.1 +cow=49.7 +elephant=55.6 +bear=59.0 +zebra=61.4 +giraffe=60.8 +backpack=12.6 +umbrella=37.1 +handbag=13.5 +tie=31.2 +suitcase=29.3 +frisbee=61.7 +skis=20.2 +snowboard=36.3 +sports ball=38.5 +kite=37.2 +baseball bat=29.9 +baseball glove=36.5 +skateboard=49.7 +surfboard=36.2 +tennis racket=47.0 +bottle=37.4 +wine glass=35.4 +cup=40.7 +fork=36.8 +knife=21.3 +spoon=15.0 +bowl=39.8 +banana=23.0 +apple=17.6 +sandwich=23.9 +orange=27.1 +broccoli=18.3 +carrot=18.0 +hot dog=27.5 +pizza=49.8 +donut=39.4 +cake=33.5 +chair=26.3 +couch=37.9 +potted plant=29.2 +bed=31.6 +dining table=24.9 +toilet=54.2 +tv=49.6 +laptop=57.2 +mouse=59.3 +remote=33.3 +keyboard=45.6 +cell phone=30.9 +microwave=54.7 +oven=32.4 +toaster=26.7 +sink=33.6 +refrigerator=49.8 +book=13.6 +clock=47.9 +vase=32.5 +scissors=27.1 +teddy bear=39.1 +hair drier=1.4 +toothbrush=25.1 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.9 +[Epoch 10] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0010_37.9000.params +[Epoch 11][Batch 99], Speed: 6.324 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.150,RCNN_SmoothL1=0.207,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 11][Batch 199], Speed: 6.284 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.151,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 11][Batch 299], Speed: 6.209 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 11][Batch 399], Speed: 6.205 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.250,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 11][Batch 499], Speed: 6.658 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 11][Batch 599], Speed: 6.165 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.754 +[Epoch 11][Batch 699], Speed: 5.642 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 799], Speed: 5.839 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 899], Speed: 6.074 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 999], Speed: 5.662 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1099], Speed: 6.130 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1199], Speed: 6.162 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1299], Speed: 6.116 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1399], Speed: 5.757 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1499], Speed: 6.378 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1599], Speed: 5.990 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1699], Speed: 6.232 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1799], Speed: 5.545 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1899], Speed: 5.886 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 1999], Speed: 5.596 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.753 +[Epoch 11][Batch 2099], Speed: 5.847 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2199], Speed: 6.178 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2299], Speed: 5.345 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2399], Speed: 5.991 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2499], Speed: 6.177 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2599], Speed: 6.117 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2699], Speed: 5.599 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2799], Speed: 5.997 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2899], Speed: 5.783 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 2999], Speed: 5.537 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 3099], Speed: 6.291 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 3199], Speed: 6.225 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 3299], Speed: 6.149 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.752 +[Epoch 11][Batch 3399], Speed: 6.039 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 3499], Speed: 6.012 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 3599], Speed: 5.858 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 3699], Speed: 5.687 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 3799], Speed: 6.000 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 3899], Speed: 5.582 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 3999], Speed: 6.182 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4099], Speed: 6.554 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4199], Speed: 5.768 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4299], Speed: 5.625 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4399], Speed: 5.713 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4499], Speed: 5.848 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4599], Speed: 6.181 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4699], Speed: 6.400 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4799], Speed: 5.692 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4899], Speed: 6.102 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.751 +[Epoch 11][Batch 4999], Speed: 6.121 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5099], Speed: 5.493 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5199], Speed: 5.487 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.249,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5299], Speed: 6.139 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5399], Speed: 5.575 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5499], Speed: 6.234 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5599], Speed: 6.219 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5699], Speed: 6.396 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5799], Speed: 5.716 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5899], Speed: 5.715 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 5999], Speed: 5.695 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 6099], Speed: 5.738 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 6199], Speed: 6.164 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 6299], Speed: 5.710 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 6399], Speed: 5.722 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 6499], Speed: 6.023 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.750 +[Epoch 11][Batch 6599], Speed: 6.154 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 6699], Speed: 5.519 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 6799], Speed: 5.554 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 6899], Speed: 5.875 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 6999], Speed: 5.624 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7099], Speed: 5.890 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7199], Speed: 6.067 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7299], Speed: 6.345 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7399], Speed: 5.638 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7499], Speed: 5.627 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7599], Speed: 6.169 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7699], Speed: 5.760 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7799], Speed: 5.359 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7899], Speed: 5.604 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 7999], Speed: 5.427 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.749 +[Epoch 11][Batch 8099], Speed: 5.565 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8199], Speed: 5.701 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8299], Speed: 6.173 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8399], Speed: 6.614 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8499], Speed: 6.129 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8599], Speed: 6.060 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8699], Speed: 5.792 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8799], Speed: 5.405 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8899], Speed: 5.336 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 8999], Speed: 5.836 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 9099], Speed: 5.714 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 9199], Speed: 5.569 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 9299], Speed: 5.926 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 9399], Speed: 5.527 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 9499], Speed: 5.717 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 9599], Speed: 5.409 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 9699], Speed: 5.905 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.748 +[Epoch 11][Batch 9799], Speed: 6.137 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 9899], Speed: 5.826 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 9999], Speed: 6.383 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10099], Speed: 5.772 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10199], Speed: 6.127 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10299], Speed: 5.442 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10399], Speed: 6.144 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10499], Speed: 5.746 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10599], Speed: 5.837 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10699], Speed: 5.918 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10799], Speed: 5.447 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10899], Speed: 5.905 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.248,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 10999], Speed: 5.444 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 11099], Speed: 5.689 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 11199], Speed: 5.710 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 11299], Speed: 5.979 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 11399], Speed: 5.794 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 11499], Speed: 5.552 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.747 +[Epoch 11][Batch 11599], Speed: 6.191 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 11699], Speed: 5.847 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 11799], Speed: 5.902 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 11899], Speed: 5.719 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 11999], Speed: 5.635 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12099], Speed: 6.178 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12199], Speed: 5.898 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12299], Speed: 5.687 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12399], Speed: 5.573 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12499], Speed: 5.660 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12599], Speed: 5.884 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12699], Speed: 5.725 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12799], Speed: 5.677 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12899], Speed: 6.214 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 12999], Speed: 5.898 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 13099], Speed: 5.501 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 13199], Speed: 5.539 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 13299], Speed: 6.335 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 13399], Speed: 6.342 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 13499], Speed: 5.666 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.746 +[Epoch 11][Batch 13599], Speed: 5.611 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 13699], Speed: 5.547 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 13799], Speed: 5.647 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 13899], Speed: 5.634 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 13999], Speed: 5.508 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 14099], Speed: 5.828 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 14199], Speed: 5.892 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 14299], Speed: 6.515 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 14399], Speed: 6.443 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 14499], Speed: 5.556 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11][Batch 14599], Speed: 5.686 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 11] Training cost: 19998.354, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.217 +[Epoch 11] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.372 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.579 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.403 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.227 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.417 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.468 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.312 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.508 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.538 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.361 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.582 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.657 +person=52.8 +bicycle=28.9 +car=42.1 +motorcycle=40.8 +airplane=61.9 +bus=52.8 +train=53.1 +truck=29.9 +boat=24.0 +traffic light=25.0 +fire hydrant=62.9 +stop sign=58.0 +parking meter=42.1 +bench=23.5 +bird=32.1 +cat=58.4 +dog=40.0 +horse=52.3 +sheep=48.5 +cow=49.6 +elephant=57.5 +bear=67.1 +zebra=60.7 +giraffe=61.1 +backpack=11.2 +umbrella=36.9 +handbag=15.0 +tie=33.8 +suitcase=30.2 +frisbee=63.3 +skis=18.3 +snowboard=30.0 +sports ball=37.6 +kite=40.3 +baseball bat=29.9 +baseball glove=35.9 +skateboard=47.4 +surfboard=34.0 +tennis racket=46.9 +bottle=37.9 +wine glass=36.8 +cup=40.4 +fork=34.1 +knife=16.0 +spoon=13.7 +bowl=37.1 +banana=22.7 +apple=16.5 +sandwich=26.4 +orange=23.3 +broccoli=21.2 +carrot=19.9 +hot dog=28.7 +pizza=45.8 +donut=42.4 +cake=27.6 +chair=26.9 +couch=35.9 +potted plant=27.3 +bed=34.0 +dining table=25.6 +toilet=53.0 +tv=49.6 +laptop=52.0 +mouse=56.2 +remote=32.4 +keyboard=33.9 +cell phone=32.6 +microwave=51.2 +oven=30.0 +toaster=35.8 +sink=33.0 +refrigerator=50.8 +book=15.2 +clock=46.6 +vase=34.7 +scissors=18.9 +teddy bear=40.3 +hair drier=5.6 +toothbrush=25.5 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.2 +[Epoch 11] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0011_37.2000.params +[Epoch 12][Batch 99], Speed: 6.154 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 12][Batch 199], Speed: 6.555 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 12][Batch 299], Speed: 6.162 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 12][Batch 399], Speed: 6.479 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 12][Batch 499], Speed: 5.701 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 12][Batch 599], Speed: 6.070 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.218,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.745 +[Epoch 12][Batch 699], Speed: 6.391 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.217,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 799], Speed: 6.146 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 899], Speed: 5.939 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 999], Speed: 6.436 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1099], Speed: 5.733 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1199], Speed: 5.909 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1299], Speed: 5.991 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1399], Speed: 5.835 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1499], Speed: 6.130 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1599], Speed: 5.854 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1699], Speed: 5.483 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1799], Speed: 5.914 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1899], Speed: 6.025 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 1999], Speed: 5.732 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 2099], Speed: 6.192 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.247,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 2199], Speed: 5.596 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.744 +[Epoch 12][Batch 2299], Speed: 5.954 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 2399], Speed: 6.108 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 2499], Speed: 5.669 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 2599], Speed: 5.961 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 2699], Speed: 6.233 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 2799], Speed: 6.065 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 2899], Speed: 6.106 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 2999], Speed: 5.948 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3099], Speed: 5.681 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3199], Speed: 6.001 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3299], Speed: 6.175 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3399], Speed: 5.939 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3499], Speed: 5.504 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3599], Speed: 6.165 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3699], Speed: 6.440 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3799], Speed: 5.976 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.743 +[Epoch 12][Batch 3899], Speed: 5.990 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.936,RCNNL1Loss=0.742 +[Epoch 12][Batch 3999], Speed: 5.988 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4099], Speed: 6.230 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4199], Speed: 5.233 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4299], Speed: 5.627 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4399], Speed: 5.705 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4499], Speed: 5.936 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4599], Speed: 5.782 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4699], Speed: 5.580 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4799], Speed: 6.184 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4899], Speed: 5.652 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 4999], Speed: 6.060 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 5099], Speed: 5.338 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 5199], Speed: 6.057 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 5299], Speed: 5.996 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 5399], Speed: 6.169 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 5499], Speed: 6.201 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 5599], Speed: 6.025 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.742 +[Epoch 12][Batch 5699], Speed: 5.837 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 5799], Speed: 5.904 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 5899], Speed: 5.838 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 5999], Speed: 5.520 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6099], Speed: 5.393 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6199], Speed: 5.644 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6299], Speed: 5.882 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6399], Speed: 6.391 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6499], Speed: 5.561 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6599], Speed: 6.483 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6699], Speed: 5.845 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6799], Speed: 5.862 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6899], Speed: 5.451 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 6999], Speed: 5.952 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 7099], Speed: 7.081 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 7199], Speed: 5.629 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 7299], Speed: 6.270 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 7399], Speed: 5.429 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.741 +[Epoch 12][Batch 7499], Speed: 5.462 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 7599], Speed: 5.768 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 7699], Speed: 5.763 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 7799], Speed: 5.792 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 7899], Speed: 6.408 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 7999], Speed: 5.885 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8099], Speed: 5.824 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.246,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8199], Speed: 5.862 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8299], Speed: 6.249 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8399], Speed: 5.604 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8499], Speed: 5.831 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8599], Speed: 5.705 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8699], Speed: 5.917 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8799], Speed: 6.189 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8899], Speed: 6.071 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 8999], Speed: 5.947 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 9099], Speed: 5.951 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 9199], Speed: 6.089 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 9299], Speed: 5.541 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.740 +[Epoch 12][Batch 9399], Speed: 5.675 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 9499], Speed: 5.979 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 9599], Speed: 6.225 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 9699], Speed: 5.825 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 9799], Speed: 5.834 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 9899], Speed: 5.568 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 9999], Speed: 6.248 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10099], Speed: 6.266 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10199], Speed: 5.628 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10299], Speed: 5.948 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10399], Speed: 5.540 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10499], Speed: 5.880 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10599], Speed: 6.207 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10699], Speed: 6.041 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10799], Speed: 5.747 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10899], Speed: 5.676 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 10999], Speed: 6.620 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 11099], Speed: 5.911 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 11199], Speed: 5.706 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 11299], Speed: 5.494 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 11399], Speed: 6.102 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 11499], Speed: 5.894 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.739 +[Epoch 12][Batch 11599], Speed: 5.585 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 11699], Speed: 6.001 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 11799], Speed: 5.545 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 11899], Speed: 5.699 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 11999], Speed: 6.370 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12099], Speed: 5.424 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12199], Speed: 5.608 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12299], Speed: 5.906 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12399], Speed: 5.987 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12499], Speed: 6.407 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12599], Speed: 6.155 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12699], Speed: 5.907 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12799], Speed: 6.436 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12899], Speed: 5.838 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 12999], Speed: 6.048 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 13099], Speed: 5.779 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 13199], Speed: 5.817 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 13299], Speed: 5.870 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 13399], Speed: 6.108 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 13499], Speed: 6.281 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 13599], Speed: 5.666 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.738 +[Epoch 12][Batch 13699], Speed: 5.839 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 13799], Speed: 5.960 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 13899], Speed: 5.527 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.215,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 13999], Speed: 6.601 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 14099], Speed: 6.134 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 14199], Speed: 5.817 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 14299], Speed: 6.014 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 14399], Speed: 6.181 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 14499], Speed: 5.767 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12][Batch 14599], Speed: 6.087 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 12] Training cost: 19811.796, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.165,RCNN_SmoothL1=0.216 +[Epoch 12] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.376 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.589 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.407 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.246 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.424 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.475 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.315 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.515 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.550 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.385 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.589 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.666 +person=52.9 +bicycle=28.6 +car=41.8 +motorcycle=43.5 +airplane=62.4 +bus=61.2 +train=54.8 +truck=34.4 +boat=23.6 +traffic light=26.0 +fire hydrant=62.4 +stop sign=63.7 +parking meter=40.8 +bench=22.0 +bird=30.7 +cat=56.5 +dog=51.8 +horse=46.1 +sheep=46.7 +cow=48.3 +elephant=50.0 +bear=61.4 +zebra=58.9 +giraffe=62.1 +backpack=13.9 +umbrella=35.8 +handbag=15.1 +tie=35.5 +suitcase=31.2 +frisbee=65.1 +skis=21.2 +snowboard=33.2 +sports ball=36.9 +kite=39.8 +baseball bat=31.5 +baseball glove=37.6 +skateboard=51.1 +surfboard=36.5 +tennis racket=47.2 +bottle=39.7 +wine glass=35.3 +cup=40.7 +fork=35.0 +knife=18.6 +spoon=18.3 +bowl=40.4 +banana=22.8 +apple=16.9 +sandwich=24.4 +orange=24.9 +broccoli=18.8 +carrot=18.6 +hot dog=28.7 +pizza=50.8 +donut=42.4 +cake=29.9 +chair=26.7 +couch=30.3 +potted plant=26.7 +bed=34.1 +dining table=24.7 +toilet=47.8 +tv=53.6 +laptop=52.5 +mouse=56.0 +remote=28.5 +keyboard=49.0 +cell phone=28.4 +microwave=51.9 +oven=30.5 +toaster=22.8 +sink=32.6 +refrigerator=50.1 +book=14.1 +clock=49.6 +vase=38.0 +scissors=24.0 +teddy bear=37.5 +hair drier=6.6 +toothbrush=21.8 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.6 +[Epoch 12] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0012_37.6000.params +[Epoch 13][Batch 99], Speed: 5.905 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 199], Speed: 5.979 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.245,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 299], Speed: 6.877 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 399], Speed: 6.262 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 499], Speed: 6.101 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 599], Speed: 6.253 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 699], Speed: 6.549 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 799], Speed: 5.866 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 899], Speed: 5.865 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.737 +[Epoch 13][Batch 999], Speed: 6.104 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1099], Speed: 6.266 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1199], Speed: 5.829 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1299], Speed: 5.371 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1399], Speed: 5.628 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1499], Speed: 5.589 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1599], Speed: 6.228 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1699], Speed: 6.219 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1799], Speed: 5.351 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1899], Speed: 5.587 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 1999], Speed: 5.732 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 2099], Speed: 5.712 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 2199], Speed: 5.874 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 2299], Speed: 6.208 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 2399], Speed: 6.040 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 2499], Speed: 5.630 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 2599], Speed: 5.530 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.736 +[Epoch 13][Batch 2699], Speed: 5.777 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 2799], Speed: 5.751 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 2899], Speed: 5.845 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 2999], Speed: 5.985 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3099], Speed: 5.608 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3199], Speed: 5.548 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3299], Speed: 6.317 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3399], Speed: 6.339 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3499], Speed: 6.090 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3599], Speed: 5.594 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3699], Speed: 6.204 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3799], Speed: 5.606 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3899], Speed: 5.733 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 3999], Speed: 6.098 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 4099], Speed: 6.047 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 4199], Speed: 5.636 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 4299], Speed: 6.373 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 4399], Speed: 6.266 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 4499], Speed: 5.956 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 4599], Speed: 5.811 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.735 +[Epoch 13][Batch 4699], Speed: 6.129 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 4799], Speed: 5.928 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 4899], Speed: 5.576 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 4999], Speed: 5.746 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5099], Speed: 5.792 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5199], Speed: 6.027 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5299], Speed: 5.771 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5399], Speed: 6.050 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5499], Speed: 5.760 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5599], Speed: 6.469 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5699], Speed: 6.609 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5799], Speed: 5.338 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5899], Speed: 6.059 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 5999], Speed: 5.827 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 6099], Speed: 6.087 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 6199], Speed: 6.348 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 6299], Speed: 5.851 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 6399], Speed: 5.535 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 6499], Speed: 5.390 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 6599], Speed: 5.985 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.244,RCNNAcc=0.937,RCNNL1Loss=0.734 +[Epoch 13][Batch 6699], Speed: 5.523 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 6799], Speed: 5.943 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 6899], Speed: 6.036 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 6999], Speed: 5.659 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7099], Speed: 5.745 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7199], Speed: 5.789 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7299], Speed: 6.336 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7399], Speed: 5.502 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7499], Speed: 6.055 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7599], Speed: 5.799 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7699], Speed: 6.149 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7799], Speed: 6.146 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7899], Speed: 6.051 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 7999], Speed: 5.582 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 8099], Speed: 6.099 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 8199], Speed: 6.146 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 8299], Speed: 5.846 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 8399], Speed: 6.160 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 8499], Speed: 6.055 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 8599], Speed: 5.547 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 8699], Speed: 5.823 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.733 +[Epoch 13][Batch 8799], Speed: 5.775 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 8899], Speed: 5.917 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 8999], Speed: 5.906 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9099], Speed: 6.305 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9199], Speed: 5.712 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9299], Speed: 6.090 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9399], Speed: 5.920 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9499], Speed: 5.851 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9599], Speed: 5.629 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9699], Speed: 6.027 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9799], Speed: 6.104 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9899], Speed: 6.237 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 9999], Speed: 5.958 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10099], Speed: 6.168 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10199], Speed: 5.894 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10299], Speed: 5.838 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10399], Speed: 6.070 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10499], Speed: 6.098 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10599], Speed: 6.330 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10699], Speed: 6.711 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10799], Speed: 5.964 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10899], Speed: 5.459 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.732 +[Epoch 13][Batch 10999], Speed: 6.139 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11099], Speed: 6.230 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11199], Speed: 6.337 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11299], Speed: 5.746 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11399], Speed: 5.805 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11499], Speed: 6.405 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11599], Speed: 5.538 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11699], Speed: 5.245 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11799], Speed: 5.600 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11899], Speed: 5.730 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 11999], Speed: 5.800 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12099], Speed: 5.510 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12199], Speed: 6.166 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12299], Speed: 5.979 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12399], Speed: 6.314 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12499], Speed: 5.563 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12599], Speed: 5.553 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12699], Speed: 5.570 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12799], Speed: 5.840 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12899], Speed: 6.242 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 12999], Speed: 5.980 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 13099], Speed: 6.008 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 13199], Speed: 6.360 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 13299], Speed: 5.397 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 13399], Speed: 5.924 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.731 +[Epoch 13][Batch 13499], Speed: 5.710 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 13599], Speed: 5.663 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 13699], Speed: 5.639 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 13799], Speed: 5.934 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 13899], Speed: 6.118 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 13999], Speed: 5.016 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.243,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 14099], Speed: 6.205 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 14199], Speed: 6.043 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 14299], Speed: 6.203 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 14399], Speed: 6.092 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 14499], Speed: 5.689 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13][Batch 14599], Speed: 5.786 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 13] Training cost: 19865.958, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.214 +[Epoch 13] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.376 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.581 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.413 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.231 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.424 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.474 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.320 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.512 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.541 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.359 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.580 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.663 +person=53.1 +bicycle=25.4 +car=43.0 +motorcycle=37.6 +airplane=62.2 +bus=61.4 +train=56.1 +truck=31.1 +boat=21.3 +traffic light=26.5 +fire hydrant=66.4 +stop sign=62.8 +parking meter=44.8 +bench=22.4 +bird=31.7 +cat=65.0 +dog=51.3 +horse=49.6 +sheep=39.9 +cow=38.6 +elephant=38.9 +bear=56.0 +zebra=62.0 +giraffe=63.4 +backpack=12.1 +umbrella=37.4 +handbag=13.1 +tie=34.1 +suitcase=35.8 +frisbee=66.1 +skis=20.9 +snowboard=34.3 +sports ball=40.3 +kite=36.3 +baseball bat=33.8 +baseball glove=34.6 +skateboard=50.6 +surfboard=34.6 +tennis racket=49.7 +bottle=36.1 +wine glass=34.7 +cup=40.5 +fork=35.2 +knife=17.3 +spoon=18.0 +bowl=36.0 +banana=20.7 +apple=14.6 +sandwich=32.1 +orange=23.0 +broccoli=11.8 +carrot=16.2 +hot dog=31.1 +pizza=45.5 +donut=37.0 +cake=30.0 +chair=26.2 +couch=37.0 +potted plant=24.4 +bed=40.7 +dining table=26.5 +toilet=49.7 +tv=52.0 +laptop=55.4 +mouse=54.8 +remote=31.7 +keyboard=49.5 +cell phone=34.0 +microwave=55.4 +oven=32.4 +toaster=45.7 +sink=33.1 +refrigerator=50.9 +book=14.8 +clock=46.3 +vase=38.1 +scissors=24.2 +teddy bear=37.8 +hair drier=2.4 +toothbrush=24.6 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.6 +[Epoch 13] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0013_37.6000.params +[Epoch 14][Batch 99], Speed: 6.351 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 199], Speed: 6.408 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 299], Speed: 6.387 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.206,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 399], Speed: 6.479 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 499], Speed: 6.081 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 599], Speed: 6.705 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 699], Speed: 5.574 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 799], Speed: 6.279 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 899], Speed: 5.167 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.730 +[Epoch 14][Batch 999], Speed: 5.952 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1099], Speed: 5.811 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1199], Speed: 6.360 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1299], Speed: 6.116 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1399], Speed: 6.385 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1499], Speed: 5.421 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1599], Speed: 6.173 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1699], Speed: 6.205 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1799], Speed: 5.871 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1899], Speed: 5.611 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 1999], Speed: 6.100 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2099], Speed: 5.583 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2199], Speed: 5.473 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2299], Speed: 5.765 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2399], Speed: 5.568 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2499], Speed: 6.305 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2599], Speed: 6.390 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2699], Speed: 5.747 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2799], Speed: 5.645 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.729 +[Epoch 14][Batch 2899], Speed: 5.982 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 2999], Speed: 6.189 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3099], Speed: 6.342 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3199], Speed: 5.828 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3299], Speed: 5.950 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3399], Speed: 6.345 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3499], Speed: 6.043 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3599], Speed: 5.436 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3699], Speed: 6.508 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3799], Speed: 5.661 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3899], Speed: 5.909 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 3999], Speed: 6.112 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4099], Speed: 6.398 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4199], Speed: 5.889 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4299], Speed: 5.635 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4399], Speed: 6.224 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4499], Speed: 5.679 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4599], Speed: 5.761 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4699], Speed: 5.606 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4799], Speed: 5.941 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4899], Speed: 5.435 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.728 +[Epoch 14][Batch 4999], Speed: 5.496 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5099], Speed: 5.753 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5199], Speed: 5.840 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5299], Speed: 5.927 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5399], Speed: 5.813 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5499], Speed: 6.310 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5599], Speed: 6.301 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5699], Speed: 5.390 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5799], Speed: 6.022 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.937,RCNNL1Loss=0.727 +[Epoch 14][Batch 5899], Speed: 6.219 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 5999], Speed: 5.875 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6099], Speed: 5.996 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6199], Speed: 5.908 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.242,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6299], Speed: 5.804 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6399], Speed: 5.936 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6499], Speed: 5.371 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6599], Speed: 5.553 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6699], Speed: 6.100 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6799], Speed: 5.992 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6899], Speed: 5.470 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 6999], Speed: 5.649 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 7099], Speed: 5.747 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.727 +[Epoch 14][Batch 7199], Speed: 6.238 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 7299], Speed: 6.137 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 7399], Speed: 6.221 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 7499], Speed: 5.887 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 7599], Speed: 6.236 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 7699], Speed: 5.796 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 7799], Speed: 5.286 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 7899], Speed: 5.892 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 7999], Speed: 5.800 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8099], Speed: 6.357 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8199], Speed: 5.580 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8299], Speed: 6.246 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8399], Speed: 6.346 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8499], Speed: 5.259 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8599], Speed: 6.041 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8699], Speed: 5.299 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8799], Speed: 5.736 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8899], Speed: 5.870 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 8999], Speed: 5.484 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 9099], Speed: 6.095 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 9199], Speed: 6.136 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 9299], Speed: 5.783 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 9399], Speed: 6.173 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 9499], Speed: 6.212 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 9599], Speed: 5.799 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 9699], Speed: 5.425 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.726 +[Epoch 14][Batch 9799], Speed: 5.804 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 9899], Speed: 5.576 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 9999], Speed: 5.634 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10099], Speed: 5.839 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10199], Speed: 6.075 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10299], Speed: 5.269 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10399], Speed: 6.542 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10499], Speed: 5.742 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10599], Speed: 5.733 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10699], Speed: 5.718 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10799], Speed: 5.533 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10899], Speed: 5.716 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 10999], Speed: 6.001 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11099], Speed: 5.562 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11199], Speed: 5.669 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11299], Speed: 5.913 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11399], Speed: 5.980 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11499], Speed: 6.280 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11599], Speed: 5.622 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11699], Speed: 5.717 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11799], Speed: 5.465 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11899], Speed: 5.953 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 11999], Speed: 6.054 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 12099], Speed: 5.460 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 12199], Speed: 5.838 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.725 +[Epoch 14][Batch 12299], Speed: 6.211 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 12399], Speed: 6.352 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 12499], Speed: 5.669 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 12599], Speed: 5.762 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 12699], Speed: 5.708 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 12799], Speed: 6.057 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 12899], Speed: 5.647 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 12999], Speed: 6.157 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13099], Speed: 5.767 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13199], Speed: 5.702 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13299], Speed: 5.458 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13399], Speed: 5.631 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13499], Speed: 5.896 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13599], Speed: 5.910 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13699], Speed: 5.492 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13799], Speed: 5.462 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13899], Speed: 5.967 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 13999], Speed: 6.394 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 14099], Speed: 6.180 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 14199], Speed: 6.001 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 14299], Speed: 5.632 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 14399], Speed: 6.042 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 14499], Speed: 6.003 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14][Batch 14599], Speed: 5.576 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.988,RPNL1Loss=0.241,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 14] Training cost: 19976.219, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213 +[Epoch 14] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.385 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.596 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.417 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.247 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.426 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.480 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.319 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.522 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.557 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.399 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.596 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.664 +person=54.1 +bicycle=28.9 +car=42.5 +motorcycle=40.6 +airplane=56.3 +bus=62.1 +train=57.4 +truck=34.8 +boat=25.1 +traffic light=26.9 +fire hydrant=66.5 +stop sign=61.4 +parking meter=41.8 +bench=22.5 +bird=34.6 +cat=64.1 +dog=56.1 +horse=51.1 +sheep=51.1 +cow=48.8 +elephant=60.4 +bear=61.8 +zebra=63.5 +giraffe=62.3 +backpack=16.5 +umbrella=37.3 +handbag=12.2 +tie=33.5 +suitcase=32.1 +frisbee=62.5 +skis=22.0 +snowboard=35.7 +sports ball=39.9 +kite=39.8 +baseball bat=30.2 +baseball glove=37.1 +skateboard=50.0 +surfboard=34.9 +tennis racket=44.1 +bottle=38.0 +wine glass=36.1 +cup=38.4 +fork=34.1 +knife=18.1 +spoon=20.1 +bowl=30.3 +banana=19.6 +apple=16.4 +sandwich=27.1 +orange=25.9 +broccoli=19.1 +carrot=21.2 +hot dog=30.4 +pizza=48.8 +donut=41.4 +cake=31.5 +chair=26.3 +couch=38.6 +potted plant=26.7 +bed=36.7 +dining table=23.9 +toilet=56.2 +tv=52.6 +laptop=55.6 +mouse=55.9 +remote=33.6 +keyboard=49.7 +cell phone=34.4 +microwave=53.7 +oven=27.3 +toaster=27.7 +sink=33.7 +refrigerator=50.9 +book=15.2 +clock=48.7 +vase=36.4 +scissors=26.1 +teddy bear=42.5 +hair drier=4.9 +toothbrush=20.9 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=38.5 +[Epoch 14] mAP 38.5 higher than current best [38.1] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 14] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0014_38.5000.params +[Epoch 15][Batch 99], Speed: 6.648 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 15][Batch 199], Speed: 6.517 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.724 +[Epoch 15][Batch 299], Speed: 6.023 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.208,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 399], Speed: 6.005 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 499], Speed: 6.330 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 599], Speed: 5.651 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 699], Speed: 5.875 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 799], Speed: 5.992 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 899], Speed: 6.395 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 999], Speed: 5.680 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1099], Speed: 6.418 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1199], Speed: 5.883 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1299], Speed: 6.772 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1399], Speed: 5.618 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1499], Speed: 5.565 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1599], Speed: 5.604 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1699], Speed: 5.373 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1799], Speed: 6.211 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1899], Speed: 5.873 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.209,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 1999], Speed: 5.985 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 2099], Speed: 6.228 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 2199], Speed: 5.681 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 2299], Speed: 6.172 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.723 +[Epoch 15][Batch 2399], Speed: 5.946 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 2499], Speed: 6.211 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 2599], Speed: 5.865 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 2699], Speed: 6.283 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 2799], Speed: 5.961 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 2899], Speed: 5.940 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 2999], Speed: 5.723 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3099], Speed: 5.505 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3199], Speed: 5.979 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3299], Speed: 5.993 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3399], Speed: 5.899 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3499], Speed: 6.112 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3599], Speed: 6.078 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.211,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3699], Speed: 5.781 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3799], Speed: 6.088 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3899], Speed: 5.787 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 3999], Speed: 5.708 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 4099], Speed: 6.135 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 4199], Speed: 6.274 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 4299], Speed: 5.659 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 4399], Speed: 5.881 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 4499], Speed: 5.312 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 4599], Speed: 5.458 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.722 +[Epoch 15][Batch 4699], Speed: 5.344 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 4799], Speed: 5.384 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.988,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 4899], Speed: 5.853 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 4999], Speed: 6.036 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5099], Speed: 6.270 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5199], Speed: 5.348 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5299], Speed: 5.955 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5399], Speed: 6.031 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5499], Speed: 6.003 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5599], Speed: 6.167 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5699], Speed: 6.298 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5799], Speed: 5.978 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5899], Speed: 6.425 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 5999], Speed: 6.058 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6099], Speed: 6.238 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6199], Speed: 5.969 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6299], Speed: 5.939 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6399], Speed: 5.926 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6499], Speed: 6.590 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6599], Speed: 6.168 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6699], Speed: 5.830 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6799], Speed: 5.670 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6899], Speed: 5.717 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 6999], Speed: 6.211 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 7099], Speed: 6.163 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 7199], Speed: 6.580 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.721 +[Epoch 15][Batch 7299], Speed: 5.513 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 7399], Speed: 5.570 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 7499], Speed: 6.154 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 7599], Speed: 6.216 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 7699], Speed: 5.755 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 7799], Speed: 6.086 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 7899], Speed: 5.954 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 7999], Speed: 5.465 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8099], Speed: 5.791 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8199], Speed: 5.711 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.240,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8299], Speed: 5.883 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8399], Speed: 5.709 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8499], Speed: 5.818 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8599], Speed: 5.677 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8699], Speed: 5.892 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8799], Speed: 6.076 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8899], Speed: 5.502 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 8999], Speed: 5.513 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9099], Speed: 5.773 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9199], Speed: 6.351 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9299], Speed: 5.451 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9399], Speed: 6.244 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9499], Speed: 6.134 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9599], Speed: 5.780 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9699], Speed: 6.478 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9799], Speed: 6.205 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9899], Speed: 5.919 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.720 +[Epoch 15][Batch 9999], Speed: 6.076 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10099], Speed: 5.844 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10199], Speed: 5.796 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10299], Speed: 5.810 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10399], Speed: 6.341 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10499], Speed: 6.649 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10599], Speed: 6.021 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10699], Speed: 5.782 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10799], Speed: 6.414 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10899], Speed: 6.072 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 10999], Speed: 6.095 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11099], Speed: 5.804 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11199], Speed: 5.798 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11299], Speed: 5.537 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11399], Speed: 5.850 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11499], Speed: 5.976 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11599], Speed: 5.589 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11699], Speed: 5.642 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11799], Speed: 5.763 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11899], Speed: 6.218 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 11999], Speed: 6.035 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 12099], Speed: 5.780 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 12199], Speed: 5.864 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 12299], Speed: 5.398 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 12399], Speed: 5.545 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 12499], Speed: 5.748 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 12599], Speed: 5.439 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 12699], Speed: 6.089 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.719 +[Epoch 15][Batch 12799], Speed: 5.643 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 12899], Speed: 5.682 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 12999], Speed: 5.684 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13099], Speed: 5.899 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13199], Speed: 6.055 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13299], Speed: 5.882 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13399], Speed: 5.427 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13499], Speed: 5.789 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13599], Speed: 5.953 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13699], Speed: 5.456 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13799], Speed: 6.361 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13899], Speed: 5.687 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 13999], Speed: 6.579 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 14099], Speed: 5.916 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 14199], Speed: 5.937 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 14299], Speed: 5.910 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 14399], Speed: 6.225 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 14499], Speed: 6.369 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15][Batch 14599], Speed: 5.618 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 15] Training cost: 19819.172, RPN_Conf=0.027,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.213 +[Epoch 15] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.375 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.572 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.409 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.237 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.414 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.471 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.317 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.513 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.540 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.371 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.581 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.670 +person=53.4 +bicycle=23.0 +car=41.0 +motorcycle=41.6 +airplane=58.8 +bus=62.2 +train=59.0 +truck=32.4 +boat=24.6 +traffic light=26.0 +fire hydrant=63.2 +stop sign=61.3 +parking meter=40.0 +bench=19.7 +bird=28.2 +cat=62.9 +dog=56.2 +horse=55.4 +sheep=43.6 +cow=48.8 +elephant=57.5 +bear=60.5 +zebra=59.9 +giraffe=61.3 +backpack=14.1 +umbrella=36.0 +handbag=15.0 +tie=32.4 +suitcase=33.5 +frisbee=63.8 +skis=18.0 +snowboard=28.0 +sports ball=40.3 +kite=35.5 +baseball bat=26.9 +baseball glove=37.3 +skateboard=50.8 +surfboard=30.0 +tennis racket=47.2 +bottle=36.8 +wine glass=34.9 +cup=40.6 +fork=36.0 +knife=19.1 +spoon=18.3 +bowl=37.0 +banana=19.4 +apple=16.2 +sandwich=29.3 +orange=27.8 +broccoli=17.3 +carrot=15.4 +hot dog=26.7 +pizza=51.3 +donut=42.1 +cake=31.0 +chair=25.1 +couch=36.0 +potted plant=26.9 +bed=36.7 +dining table=26.2 +toilet=53.3 +tv=51.0 +laptop=55.3 +mouse=56.2 +remote=29.9 +keyboard=48.0 +cell phone=30.4 +microwave=46.4 +oven=28.5 +toaster=21.4 +sink=32.8 +refrigerator=48.9 +book=14.9 +clock=50.0 +vase=37.4 +scissors=22.7 +teddy bear=38.7 +hair drier=7.4 +toothbrush=24.1 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.5 +[Epoch 15] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0015_37.5000.params +[Epoch 16][Batch 99], Speed: 6.082 samples/sec, RPN_Conf=0.027,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 16][Batch 199], Speed: 6.242 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 16][Batch 299], Speed: 6.167 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 16][Batch 399], Speed: 6.363 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 16][Batch 499], Speed: 5.806 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 16][Batch 599], Speed: 5.716 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 16][Batch 699], Speed: 6.313 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 16][Batch 799], Speed: 5.831 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.718 +[Epoch 16][Batch 899], Speed: 5.818 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 999], Speed: 5.694 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1099], Speed: 6.004 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1199], Speed: 5.674 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1299], Speed: 6.159 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1399], Speed: 5.416 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1499], Speed: 5.907 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1599], Speed: 5.674 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1699], Speed: 6.221 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1799], Speed: 5.872 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1899], Speed: 6.289 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 1999], Speed: 5.531 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2099], Speed: 6.254 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2199], Speed: 6.094 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2299], Speed: 6.003 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2399], Speed: 6.088 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2499], Speed: 6.014 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2599], Speed: 5.577 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.239,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2699], Speed: 5.631 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2799], Speed: 5.554 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2899], Speed: 5.390 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 2999], Speed: 5.700 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 3099], Speed: 6.128 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.717 +[Epoch 16][Batch 3199], Speed: 6.104 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 3299], Speed: 5.805 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 3399], Speed: 5.643 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 3499], Speed: 6.010 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 3599], Speed: 6.559 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 3699], Speed: 5.835 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 3799], Speed: 5.746 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 3899], Speed: 6.113 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 3999], Speed: 6.454 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4099], Speed: 5.656 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4199], Speed: 5.667 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4299], Speed: 5.421 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4399], Speed: 5.884 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4499], Speed: 5.943 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4599], Speed: 5.993 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4699], Speed: 5.947 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4799], Speed: 6.109 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4899], Speed: 5.973 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 4999], Speed: 5.589 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5099], Speed: 5.855 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5199], Speed: 5.987 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5299], Speed: 6.125 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5399], Speed: 5.316 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5499], Speed: 5.690 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5599], Speed: 5.556 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5699], Speed: 5.975 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5799], Speed: 6.121 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5899], Speed: 5.931 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.716 +[Epoch 16][Batch 5999], Speed: 6.297 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6099], Speed: 5.490 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6199], Speed: 5.947 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6299], Speed: 5.672 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6399], Speed: 5.571 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6499], Speed: 5.993 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6599], Speed: 5.623 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6699], Speed: 6.446 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6799], Speed: 5.568 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6899], Speed: 5.890 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 6999], Speed: 6.011 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7099], Speed: 6.087 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7199], Speed: 5.822 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7299], Speed: 5.909 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7399], Speed: 5.528 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7499], Speed: 5.968 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7599], Speed: 5.427 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7699], Speed: 6.015 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7799], Speed: 5.922 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7899], Speed: 5.887 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 7999], Speed: 5.590 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8099], Speed: 5.903 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8199], Speed: 6.174 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8299], Speed: 6.100 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8399], Speed: 5.905 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8499], Speed: 6.183 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8599], Speed: 5.946 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8699], Speed: 6.369 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8799], Speed: 5.611 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.715 +[Epoch 16][Batch 8899], Speed: 5.579 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 8999], Speed: 6.134 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9099], Speed: 6.230 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9199], Speed: 5.754 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9299], Speed: 5.407 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9399], Speed: 5.696 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9499], Speed: 5.667 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9599], Speed: 6.235 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9699], Speed: 5.437 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9799], Speed: 6.350 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9899], Speed: 5.546 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 9999], Speed: 6.476 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10099], Speed: 6.733 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10199], Speed: 6.064 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10299], Speed: 5.869 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10399], Speed: 5.814 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10499], Speed: 5.898 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10599], Speed: 5.762 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10699], Speed: 6.162 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10799], Speed: 5.946 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10899], Speed: 5.852 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 10999], Speed: 6.144 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11099], Speed: 6.010 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11199], Speed: 6.134 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11299], Speed: 5.619 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11399], Speed: 5.534 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11499], Speed: 6.169 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11599], Speed: 5.568 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11699], Speed: 5.870 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11799], Speed: 6.280 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11899], Speed: 6.465 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 11999], Speed: 5.823 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 12099], Speed: 5.642 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 12199], Speed: 5.695 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.238,RCNNAcc=0.938,RCNNL1Loss=0.714 +[Epoch 16][Batch 12299], Speed: 6.109 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 12399], Speed: 6.036 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 12499], Speed: 5.467 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 12599], Speed: 5.969 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 12699], Speed: 5.809 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 12799], Speed: 5.922 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 12899], Speed: 5.849 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 12999], Speed: 5.346 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13099], Speed: 5.562 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13199], Speed: 5.921 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13299], Speed: 6.677 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13399], Speed: 5.759 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13499], Speed: 5.702 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13599], Speed: 5.573 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13699], Speed: 5.867 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13799], Speed: 5.628 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13899], Speed: 5.675 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 13999], Speed: 6.353 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 14099], Speed: 5.917 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 14199], Speed: 5.616 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 14299], Speed: 5.760 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 14399], Speed: 5.553 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 14499], Speed: 5.478 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16][Batch 14599], Speed: 6.205 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 16] Training cost: 19956.256, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.212 +[Epoch 16] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.371 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.567 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.407 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.231 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.403 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.480 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.313 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.512 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.544 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.374 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.584 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.665 +person=51.9 +bicycle=29.9 +car=41.9 +motorcycle=42.5 +airplane=57.6 +bus=60.9 +train=55.3 +truck=25.5 +boat=21.3 +traffic light=24.4 +fire hydrant=56.6 +stop sign=60.2 +parking meter=43.5 +bench=22.7 +bird=31.6 +cat=56.3 +dog=53.9 +horse=48.3 +sheep=48.4 +cow=41.6 +elephant=53.7 +bear=60.3 +zebra=63.2 +giraffe=66.1 +backpack=13.0 +umbrella=36.2 +handbag=15.7 +tie=33.1 +suitcase=34.6 +frisbee=63.8 +skis=22.4 +snowboard=33.3 +sports ball=38.0 +kite=38.8 +baseball bat=28.7 +baseball glove=34.9 +skateboard=50.2 +surfboard=30.2 +tennis racket=46.9 +bottle=34.8 +wine glass=29.5 +cup=37.3 +fork=34.4 +knife=18.1 +spoon=14.6 +bowl=35.1 +banana=22.5 +apple=17.9 +sandwich=28.4 +orange=27.2 +broccoli=19.4 +carrot=18.5 +hot dog=34.3 +pizza=47.5 +donut=39.5 +cake=32.2 +chair=26.8 +couch=37.2 +potted plant=26.6 +bed=36.6 +dining table=25.9 +toilet=51.9 +tv=52.9 +laptop=59.1 +mouse=57.1 +remote=29.2 +keyboard=46.9 +cell phone=32.8 +microwave=46.1 +oven=27.7 +toaster=25.7 +sink=34.5 +refrigerator=48.4 +book=13.7 +clock=48.8 +vase=35.9 +scissors=15.4 +teddy bear=36.9 +hair drier=5.1 +toothbrush=18.6 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.1 +[Epoch 16] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0016_37.1000.params +[Epoch 17][Batch 99], Speed: 5.834 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.044,RCNN_CrossEntropy=0.164,RCNN_SmoothL1=0.219,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 17][Batch 199], Speed: 6.213 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.214,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 17][Batch 299], Speed: 6.527 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 17][Batch 399], Speed: 6.153 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 17][Batch 499], Speed: 6.060 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 17][Batch 599], Speed: 5.838 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 17][Batch 699], Speed: 6.619 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.713 +[Epoch 17][Batch 799], Speed: 5.553 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 899], Speed: 5.341 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 999], Speed: 5.786 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1099], Speed: 6.063 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1199], Speed: 6.810 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1299], Speed: 5.785 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1399], Speed: 5.612 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1499], Speed: 5.824 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1599], Speed: 6.111 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1699], Speed: 5.375 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1799], Speed: 5.666 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1899], Speed: 5.992 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 1999], Speed: 5.763 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2099], Speed: 5.721 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2199], Speed: 6.271 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2299], Speed: 5.725 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2399], Speed: 5.774 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2499], Speed: 5.794 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2599], Speed: 5.839 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2699], Speed: 5.999 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2799], Speed: 5.870 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2899], Speed: 6.304 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 2999], Speed: 5.673 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 3099], Speed: 5.587 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 3199], Speed: 5.949 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 3299], Speed: 5.732 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.712 +[Epoch 17][Batch 3399], Speed: 5.623 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.938,RCNNL1Loss=0.711 +[Epoch 17][Batch 3499], Speed: 5.370 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 3599], Speed: 5.730 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 3699], Speed: 6.331 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 3799], Speed: 6.174 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 3899], Speed: 6.189 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 3999], Speed: 6.065 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4099], Speed: 5.857 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4199], Speed: 5.732 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4299], Speed: 5.957 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4399], Speed: 5.997 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4499], Speed: 5.776 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4599], Speed: 5.462 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4699], Speed: 6.467 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4799], Speed: 6.323 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4899], Speed: 5.772 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 4999], Speed: 5.495 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5099], Speed: 6.033 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5199], Speed: 5.620 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5299], Speed: 5.228 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5399], Speed: 5.566 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5499], Speed: 5.876 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5599], Speed: 5.916 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5699], Speed: 6.073 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5799], Speed: 5.777 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5899], Speed: 6.242 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 5999], Speed: 6.269 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 6099], Speed: 5.766 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 6199], Speed: 5.753 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.711 +[Epoch 17][Batch 6299], Speed: 5.815 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 6399], Speed: 5.433 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 6499], Speed: 5.944 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 6599], Speed: 6.387 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 6699], Speed: 6.562 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 6799], Speed: 5.770 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 6899], Speed: 5.840 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 6999], Speed: 6.180 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.237,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7099], Speed: 5.556 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7199], Speed: 5.337 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7299], Speed: 6.120 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7399], Speed: 6.092 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7499], Speed: 5.767 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7599], Speed: 5.684 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7699], Speed: 5.636 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7799], Speed: 5.984 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7899], Speed: 5.226 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 7999], Speed: 6.020 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8099], Speed: 5.778 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8199], Speed: 6.267 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8299], Speed: 6.204 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8399], Speed: 5.860 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8499], Speed: 5.893 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8599], Speed: 5.787 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8699], Speed: 5.425 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8799], Speed: 6.115 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8899], Speed: 6.214 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 8999], Speed: 5.970 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 9099], Speed: 5.695 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 9199], Speed: 6.340 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 9299], Speed: 5.344 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 9399], Speed: 5.647 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 9499], Speed: 5.546 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.710 +[Epoch 17][Batch 9599], Speed: 5.849 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 9699], Speed: 5.972 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 9799], Speed: 5.633 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 9899], Speed: 6.367 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 9999], Speed: 5.990 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10099], Speed: 6.066 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10199], Speed: 5.843 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10299], Speed: 6.126 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10399], Speed: 6.418 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10499], Speed: 6.141 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10599], Speed: 5.767 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10699], Speed: 5.824 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10799], Speed: 5.867 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10899], Speed: 6.240 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 10999], Speed: 5.885 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11099], Speed: 5.969 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11199], Speed: 6.135 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11299], Speed: 5.510 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11399], Speed: 5.435 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11499], Speed: 5.953 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11599], Speed: 5.787 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11699], Speed: 5.185 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11799], Speed: 5.813 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11899], Speed: 5.927 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 11999], Speed: 5.910 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12099], Speed: 6.206 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12199], Speed: 5.747 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12299], Speed: 6.164 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12399], Speed: 5.571 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12499], Speed: 5.941 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12599], Speed: 5.878 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12699], Speed: 5.741 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12799], Speed: 5.985 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12899], Speed: 6.169 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 12999], Speed: 6.045 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 13099], Speed: 5.861 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 13199], Speed: 5.905 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.709 +[Epoch 17][Batch 13299], Speed: 5.532 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 13399], Speed: 5.857 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 13499], Speed: 5.493 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 13599], Speed: 5.737 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 13699], Speed: 6.099 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 13799], Speed: 5.831 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 13899], Speed: 6.159 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 13999], Speed: 6.016 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 14099], Speed: 6.069 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 14199], Speed: 5.308 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 14299], Speed: 6.163 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 14399], Speed: 6.575 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 14499], Speed: 5.302 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17][Batch 14599], Speed: 5.614 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 17] Training cost: 19968.589, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.163,RCNN_SmoothL1=0.211 +[Epoch 17] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.387 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.591 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.421 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.242 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.430 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.503 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.323 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.521 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.551 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.369 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.596 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.676 +person=53.6 +bicycle=30.1 +car=41.5 +motorcycle=38.9 +airplane=50.4 +bus=63.4 +train=61.4 +truck=32.6 +boat=23.2 +traffic light=25.1 +fire hydrant=65.1 +stop sign=62.7 +parking meter=42.4 +bench=23.1 +bird=30.1 +cat=59.9 +dog=50.8 +horse=45.5 +sheep=49.9 +cow=46.4 +elephant=58.7 +bear=66.8 +zebra=61.7 +giraffe=63.2 +backpack=14.2 +umbrella=38.1 +handbag=14.5 +tie=30.2 +suitcase=23.7 +frisbee=63.3 +skis=20.7 +snowboard=36.7 +sports ball=39.8 +kite=36.7 +baseball bat=30.7 +baseball glove=39.9 +skateboard=50.0 +surfboard=35.5 +tennis racket=54.0 +bottle=37.7 +wine glass=35.1 +cup=41.1 +fork=35.9 +knife=18.5 +spoon=22.3 +bowl=39.4 +banana=24.4 +apple=19.2 +sandwich=29.4 +orange=27.3 +broccoli=18.2 +carrot=18.2 +hot dog=37.4 +pizza=50.5 +donut=41.1 +cake=31.2 +chair=27.0 +couch=39.4 +potted plant=27.0 +bed=36.8 +dining table=26.1 +toilet=53.8 +tv=52.0 +laptop=58.5 +mouse=59.8 +remote=34.5 +keyboard=46.9 +cell phone=33.0 +microwave=54.4 +oven=32.3 +toaster=37.7 +sink=34.1 +refrigerator=44.6 +book=13.8 +clock=49.5 +vase=37.7 +scissors=25.7 +teddy bear=43.7 +hair drier=6.1 +toothbrush=19.5 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=38.7 +[Epoch 17] mAP 38.7 higher than current best [38.5] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 17] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0017_38.7000.params +[Epoch 18][Batch 99], Speed: 6.271 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 199], Speed: 5.883 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.212,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 299], Speed: 5.734 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.043,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.214,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 399], Speed: 6.045 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 499], Speed: 6.431 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.211,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 599], Speed: 5.843 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 699], Speed: 5.747 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 799], Speed: 5.786 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 899], Speed: 6.363 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 999], Speed: 5.702 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 1099], Speed: 5.929 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 1199], Speed: 5.612 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 1299], Speed: 5.927 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 1399], Speed: 5.938 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 1499], Speed: 5.939 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 1599], Speed: 5.460 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 1699], Speed: 5.428 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.708 +[Epoch 18][Batch 1799], Speed: 6.034 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 1899], Speed: 5.821 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 1999], Speed: 5.866 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2099], Speed: 5.937 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2199], Speed: 6.112 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2299], Speed: 5.712 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2399], Speed: 6.516 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2499], Speed: 5.855 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2599], Speed: 6.200 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2699], Speed: 5.711 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2799], Speed: 6.196 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2899], Speed: 5.834 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 2999], Speed: 5.610 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3099], Speed: 5.263 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3199], Speed: 6.103 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3299], Speed: 5.877 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3399], Speed: 5.950 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3499], Speed: 5.935 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3599], Speed: 5.888 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.236,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3699], Speed: 5.732 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3799], Speed: 6.062 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3899], Speed: 6.490 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 3999], Speed: 5.647 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 4099], Speed: 6.783 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 4199], Speed: 5.582 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 4299], Speed: 5.784 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 4399], Speed: 5.595 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 4499], Speed: 5.368 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 4599], Speed: 5.961 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 4699], Speed: 6.123 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.707 +[Epoch 18][Batch 4799], Speed: 6.378 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 4899], Speed: 5.492 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 4999], Speed: 5.601 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5099], Speed: 5.832 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5199], Speed: 6.176 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5299], Speed: 5.845 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5399], Speed: 5.238 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5499], Speed: 5.935 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5599], Speed: 5.708 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5699], Speed: 5.747 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5799], Speed: 6.195 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5899], Speed: 5.673 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 5999], Speed: 6.351 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6099], Speed: 5.535 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6199], Speed: 5.604 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6299], Speed: 5.787 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6399], Speed: 6.111 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6499], Speed: 5.447 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6599], Speed: 5.487 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6699], Speed: 5.869 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6799], Speed: 6.130 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6899], Speed: 5.829 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 6999], Speed: 5.689 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7099], Speed: 5.761 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7199], Speed: 6.129 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7299], Speed: 5.966 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7399], Speed: 5.838 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7499], Speed: 5.910 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7599], Speed: 5.922 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7699], Speed: 5.463 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7799], Speed: 6.117 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7899], Speed: 6.056 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 7999], Speed: 6.103 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 8099], Speed: 5.841 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.706 +[Epoch 18][Batch 8199], Speed: 6.015 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 8299], Speed: 6.378 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 8399], Speed: 5.390 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 8499], Speed: 5.354 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 8599], Speed: 5.743 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 8699], Speed: 6.132 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 8799], Speed: 6.066 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 8899], Speed: 6.609 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 8999], Speed: 5.617 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9099], Speed: 5.419 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9199], Speed: 6.169 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9299], Speed: 5.872 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9399], Speed: 5.673 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9499], Speed: 6.096 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9599], Speed: 5.733 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9699], Speed: 5.996 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9799], Speed: 6.025 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9899], Speed: 5.814 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 9999], Speed: 6.254 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10099], Speed: 5.858 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10199], Speed: 5.532 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10299], Speed: 5.726 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10399], Speed: 5.522 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10499], Speed: 6.333 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10599], Speed: 5.717 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10699], Speed: 5.549 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10799], Speed: 5.996 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10899], Speed: 5.603 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 10999], Speed: 5.759 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11099], Speed: 6.179 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11199], Speed: 6.019 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11299], Speed: 6.153 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11399], Speed: 5.715 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11499], Speed: 6.248 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11599], Speed: 6.272 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11699], Speed: 6.172 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11799], Speed: 5.899 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11899], Speed: 5.895 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.705 +[Epoch 18][Batch 11999], Speed: 6.017 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12099], Speed: 5.863 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12199], Speed: 5.952 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12299], Speed: 6.264 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12399], Speed: 5.667 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12499], Speed: 5.526 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12599], Speed: 5.920 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12699], Speed: 5.787 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12799], Speed: 5.981 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12899], Speed: 5.915 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 12999], Speed: 6.018 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13099], Speed: 6.284 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13199], Speed: 5.481 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13299], Speed: 5.710 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13399], Speed: 5.743 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13499], Speed: 6.220 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13599], Speed: 6.005 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13699], Speed: 5.685 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13799], Speed: 5.534 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13899], Speed: 5.692 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 13999], Speed: 5.852 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 14099], Speed: 5.784 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 14199], Speed: 5.570 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 14299], Speed: 5.972 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 14399], Speed: 5.205 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 14499], Speed: 6.105 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18][Batch 14599], Speed: 6.238 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 18] Training cost: 19982.258, RPN_Conf=0.026,RPN_SmoothL1=0.042,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.210 +[Epoch 18] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.383 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.591 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.413 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.240 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.429 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.476 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.317 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.511 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.542 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.369 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.588 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.649 +person=53.1 +bicycle=28.5 +car=44.6 +motorcycle=42.4 +airplane=62.5 +bus=61.5 +train=60.7 +truck=30.3 +boat=24.8 +traffic light=25.9 +fire hydrant=61.7 +stop sign=60.8 +parking meter=39.1 +bench=21.5 +bird=31.2 +cat=58.9 +dog=53.3 +horse=52.4 +sheep=46.1 +cow=44.5 +elephant=58.7 +bear=57.3 +zebra=64.9 +giraffe=59.4 +backpack=14.8 +umbrella=35.6 +handbag=14.3 +tie=34.7 +suitcase=36.5 +frisbee=63.5 +skis=19.2 +snowboard=35.9 +sports ball=43.5 +kite=37.5 +baseball bat=30.9 +baseball glove=36.4 +skateboard=52.1 +surfboard=36.5 +tennis racket=47.2 +bottle=37.2 +wine glass=34.0 +cup=40.6 +fork=32.0 +knife=21.3 +spoon=17.1 +bowl=36.5 +banana=22.3 +apple=16.2 +sandwich=32.9 +orange=27.4 +broccoli=21.4 +carrot=19.9 +hot dog=28.2 +pizza=49.0 +donut=42.2 +cake=29.9 +chair=27.6 +couch=32.7 +potted plant=24.2 +bed=38.7 +dining table=24.0 +toilet=53.5 +tv=51.6 +laptop=56.6 +mouse=59.8 +remote=31.9 +keyboard=47.4 +cell phone=30.0 +microwave=54.3 +oven=29.0 +toaster=30.7 +sink=34.7 +refrigerator=52.9 +book=16.4 +clock=46.7 +vase=37.1 +scissors=21.8 +teddy bear=35.9 +hair drier=5.9 +toothbrush=26.9 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=38.3 +[Epoch 18] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0018_38.3000.params +[Epoch 19][Batch 99], Speed: 6.638 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 199], Speed: 6.355 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.205,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 299], Speed: 5.941 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.204,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 399], Speed: 5.873 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.150,RCNN_SmoothL1=0.205,RPNAcc=0.989,RPNL1Loss=0.235,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 499], Speed: 5.967 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.151,RCNN_SmoothL1=0.205,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 599], Speed: 6.344 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.151,RCNN_SmoothL1=0.206,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 699], Speed: 6.107 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 799], Speed: 6.081 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.206,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 899], Speed: 6.257 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 999], Speed: 5.709 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.704 +[Epoch 19][Batch 1099], Speed: 6.448 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1199], Speed: 5.727 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1299], Speed: 5.737 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.206,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1399], Speed: 6.245 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1499], Speed: 5.630 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1599], Speed: 5.705 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1699], Speed: 5.779 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1799], Speed: 6.396 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1899], Speed: 5.765 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 1999], Speed: 5.393 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2099], Speed: 6.315 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2199], Speed: 5.665 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.153,RCNN_SmoothL1=0.206,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2299], Speed: 5.690 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.040,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2399], Speed: 5.879 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2499], Speed: 5.628 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2599], Speed: 6.211 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2699], Speed: 6.014 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2799], Speed: 5.462 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2899], Speed: 5.877 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 2999], Speed: 5.621 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3099], Speed: 5.668 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3199], Speed: 5.833 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3299], Speed: 6.060 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3399], Speed: 5.940 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3499], Speed: 6.574 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3599], Speed: 6.362 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3699], Speed: 6.078 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3799], Speed: 6.109 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3899], Speed: 6.165 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.154,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 3999], Speed: 6.297 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 4099], Speed: 5.618 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.703 +[Epoch 19][Batch 4199], Speed: 5.816 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 4299], Speed: 5.771 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.155,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 4399], Speed: 6.011 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 4499], Speed: 5.768 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 4599], Speed: 6.150 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 4699], Speed: 5.450 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 4799], Speed: 5.853 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 4899], Speed: 6.096 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 4999], Speed: 5.679 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5099], Speed: 6.287 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5199], Speed: 5.927 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5299], Speed: 6.391 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.156,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5399], Speed: 5.198 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5499], Speed: 6.014 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5599], Speed: 6.233 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5699], Speed: 6.250 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5799], Speed: 5.356 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5899], Speed: 5.876 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 5999], Speed: 5.676 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6099], Speed: 5.744 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6199], Speed: 6.062 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6299], Speed: 5.672 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6399], Speed: 5.321 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6499], Speed: 5.834 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.207,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6599], Speed: 5.616 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6699], Speed: 5.840 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.157,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6799], Speed: 6.138 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6899], Speed: 6.296 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 6999], Speed: 6.009 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 7099], Speed: 5.907 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 7199], Speed: 6.195 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 7299], Speed: 6.037 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 7399], Speed: 6.136 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 7499], Speed: 6.087 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 7599], Speed: 5.944 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 7699], Speed: 6.102 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.702 +[Epoch 19][Batch 7799], Speed: 5.642 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 7899], Speed: 6.351 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 7999], Speed: 5.528 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8099], Speed: 5.926 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.158,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8199], Speed: 5.777 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8299], Speed: 5.331 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8399], Speed: 5.636 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8499], Speed: 5.398 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8599], Speed: 5.768 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8699], Speed: 5.641 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8799], Speed: 6.179 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8899], Speed: 5.869 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 8999], Speed: 6.243 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9099], Speed: 5.621 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9199], Speed: 6.401 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9299], Speed: 6.264 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9399], Speed: 5.745 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9499], Speed: 6.781 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9599], Speed: 5.918 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9699], Speed: 5.974 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9799], Speed: 5.746 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9899], Speed: 6.028 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.159,RCNN_SmoothL1=0.208,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 9999], Speed: 5.701 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10099], Speed: 5.517 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10199], Speed: 5.740 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10299], Speed: 5.767 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10399], Speed: 5.852 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10499], Speed: 5.916 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10599], Speed: 5.489 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10699], Speed: 5.860 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10799], Speed: 5.471 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10899], Speed: 5.748 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 10999], Speed: 5.705 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11099], Speed: 6.123 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11199], Speed: 5.818 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11299], Speed: 5.747 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.160,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11399], Speed: 5.869 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11499], Speed: 6.481 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11599], Speed: 5.880 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11699], Speed: 6.046 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11799], Speed: 5.683 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.701 +[Epoch 19][Batch 11899], Speed: 6.003 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 11999], Speed: 6.154 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12099], Speed: 5.644 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.234,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12199], Speed: 5.777 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12299], Speed: 5.620 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12399], Speed: 5.831 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12499], Speed: 6.229 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12599], Speed: 6.006 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12699], Speed: 5.747 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12799], Speed: 5.690 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12899], Speed: 6.445 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.161,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 12999], Speed: 5.741 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13099], Speed: 5.995 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13199], Speed: 6.193 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13299], Speed: 6.008 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13399], Speed: 5.913 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13499], Speed: 5.427 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13599], Speed: 5.405 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13699], Speed: 6.045 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13799], Speed: 5.761 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13899], Speed: 5.600 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 13999], Speed: 6.067 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 14099], Speed: 5.900 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 14199], Speed: 5.622 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 14299], Speed: 5.912 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 14399], Speed: 5.985 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 14499], Speed: 6.207 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19][Batch 14599], Speed: 5.931 samples/sec, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 19] Training cost: 19893.117, RPN_Conf=0.026,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.209 +[Epoch 19] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.375 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.581 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.407 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.245 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.418 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.471 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.316 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.515 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.547 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.392 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.582 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.655 +person=53.1 +bicycle=26.5 +car=43.3 +motorcycle=41.4 +airplane=52.1 +bus=58.2 +train=53.5 +truck=30.2 +boat=23.1 +traffic light=26.6 +fire hydrant=66.7 +stop sign=63.9 +parking meter=44.3 +bench=22.1 +bird=27.2 +cat=62.9 +dog=53.9 +horse=52.1 +sheep=48.5 +cow=54.7 +elephant=58.9 +bear=44.2 +zebra=60.5 +giraffe=62.4 +backpack=13.8 +umbrella=33.5 +handbag=12.3 +tie=29.5 +suitcase=31.5 +frisbee=63.3 +skis=21.1 +snowboard=31.0 +sports ball=43.4 +kite=33.0 +baseball bat=33.6 +baseball glove=38.1 +skateboard=52.9 +surfboard=34.5 +tennis racket=49.0 +bottle=37.1 +wine glass=34.7 +cup=41.1 +fork=34.4 +knife=16.8 +spoon=17.8 +bowl=38.8 +banana=22.3 +apple=16.2 +sandwich=24.5 +orange=25.8 +broccoli=18.2 +carrot=14.7 +hot dog=24.0 +pizza=48.6 +donut=42.9 +cake=36.1 +chair=24.7 +couch=36.6 +potted plant=24.5 +bed=32.1 +dining table=22.6 +toilet=51.3 +tv=52.8 +laptop=54.1 +mouse=59.3 +remote=32.5 +keyboard=44.0 +cell phone=31.1 +microwave=53.0 +oven=29.7 +toaster=25.3 +sink=36.7 +refrigerator=49.8 +book=15.7 +clock=46.3 +vase=36.0 +scissors=23.7 +teddy bear=38.6 +hair drier=8.4 +toothbrush=24.1 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=37.5 +[Epoch 19] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0019_37.5000.params +[Epoch 20] Set learning rate to 0.001 +[Epoch 20][Batch 99], Speed: 6.289 samples/sec, RPN_Conf=0.025,RPN_SmoothL1=0.041,RCNN_CrossEntropy=0.162,RCNN_SmoothL1=0.213,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 20][Batch 199], Speed: 6.344 samples/sec, RPN_Conf=0.024,RPN_SmoothL1=0.039,RCNN_CrossEntropy=0.152,RCNN_SmoothL1=0.204,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 20][Batch 299], Speed: 6.107 samples/sec, RPN_Conf=0.023,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.148,RCNN_SmoothL1=0.201,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 20][Batch 399], Speed: 6.324 samples/sec, RPN_Conf=0.023,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.145,RCNN_SmoothL1=0.198,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 20][Batch 499], Speed: 5.697 samples/sec, RPN_Conf=0.023,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.145,RCNN_SmoothL1=0.198,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 20][Batch 599], Speed: 5.867 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.142,RCNN_SmoothL1=0.195,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 20][Batch 699], Speed: 6.438 samples/sec, RPN_Conf=0.023,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.143,RCNN_SmoothL1=0.197,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.700 +[Epoch 20][Batch 799], Speed: 5.939 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.142,RCNN_SmoothL1=0.196,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 899], Speed: 5.594 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.142,RCNN_SmoothL1=0.197,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 999], Speed: 6.283 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.141,RCNN_SmoothL1=0.196,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1099], Speed: 5.993 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.140,RCNN_SmoothL1=0.196,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1199], Speed: 5.792 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.140,RCNN_SmoothL1=0.196,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1299], Speed: 5.320 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.139,RCNN_SmoothL1=0.196,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1399], Speed: 5.876 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.139,RCNN_SmoothL1=0.195,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1499], Speed: 5.790 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.138,RCNN_SmoothL1=0.195,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1599], Speed: 6.194 samples/sec, RPN_Conf=0.022,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.137,RCNN_SmoothL1=0.194,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1699], Speed: 6.063 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.137,RCNN_SmoothL1=0.194,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1799], Speed: 6.123 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.136,RCNN_SmoothL1=0.193,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1899], Speed: 5.648 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.136,RCNN_SmoothL1=0.193,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 1999], Speed: 6.059 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.038,RCNN_CrossEntropy=0.135,RCNN_SmoothL1=0.192,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 2099], Speed: 6.134 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.135,RCNN_SmoothL1=0.192,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 2199], Speed: 6.179 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.135,RCNN_SmoothL1=0.192,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 2299], Speed: 6.324 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.134,RCNN_SmoothL1=0.192,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 2399], Speed: 6.248 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.134,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 2499], Speed: 6.276 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.133,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 2599], Speed: 5.571 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.133,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.699 +[Epoch 20][Batch 2699], Speed: 5.718 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.133,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 2799], Speed: 5.899 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.133,RCNN_SmoothL1=0.192,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 2899], Speed: 5.333 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.133,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 2999], Speed: 5.858 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.133,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3099], Speed: 6.062 samples/sec, RPN_Conf=0.021,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.133,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3199], Speed: 5.991 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.132,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3299], Speed: 5.458 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.132,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3399], Speed: 5.932 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.132,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3499], Speed: 5.498 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.132,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3599], Speed: 5.738 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.132,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3699], Speed: 5.991 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.131,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3799], Speed: 5.966 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.131,RCNN_SmoothL1=0.191,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3899], Speed: 6.111 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.131,RCNN_SmoothL1=0.190,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 3999], Speed: 6.107 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.131,RCNN_SmoothL1=0.190,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 4099], Speed: 5.838 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.131,RCNN_SmoothL1=0.190,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 4199], Speed: 6.077 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.130,RCNN_SmoothL1=0.190,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.698 +[Epoch 20][Batch 4299], Speed: 5.517 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.130,RCNN_SmoothL1=0.190,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 4399], Speed: 5.700 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.130,RCNN_SmoothL1=0.190,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 4499], Speed: 5.830 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.130,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.233,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 4599], Speed: 5.946 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.129,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 4699], Speed: 6.004 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.129,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 4799], Speed: 5.795 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.129,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 4899], Speed: 6.080 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.129,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 4999], Speed: 5.385 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.129,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 5099], Speed: 5.997 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.129,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 5199], Speed: 6.305 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.129,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 5299], Speed: 5.699 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.129,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 5399], Speed: 6.370 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.189,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 5499], Speed: 6.224 samples/sec, RPN_Conf=0.020,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 5599], Speed: 5.273 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.939,RCNNL1Loss=0.697 +[Epoch 20][Batch 5699], Speed: 5.917 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.697 +[Epoch 20][Batch 5799], Speed: 5.899 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.697 +[Epoch 20][Batch 5899], Speed: 5.779 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 5999], Speed: 6.031 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6099], Speed: 6.048 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6199], Speed: 6.041 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6299], Speed: 5.504 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6399], Speed: 5.498 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.037,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6499], Speed: 5.659 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.128,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6599], Speed: 5.507 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6699], Speed: 6.080 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6799], Speed: 5.898 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6899], Speed: 5.960 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 6999], Speed: 6.286 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 7099], Speed: 6.283 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 7199], Speed: 5.565 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 7299], Speed: 6.000 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 7399], Speed: 5.990 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.696 +[Epoch 20][Batch 7499], Speed: 6.269 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.127,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 7599], Speed: 5.667 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 7699], Speed: 5.629 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 7799], Speed: 6.295 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.188,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 7899], Speed: 5.883 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 7999], Speed: 6.122 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8099], Speed: 5.775 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8199], Speed: 6.095 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8299], Speed: 5.675 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8399], Speed: 5.943 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8499], Speed: 6.445 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8599], Speed: 5.980 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8699], Speed: 6.134 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8799], Speed: 5.822 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8899], Speed: 6.440 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 8999], Speed: 6.003 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 9099], Speed: 5.617 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.126,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.695 +[Epoch 20][Batch 9199], Speed: 5.983 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 9299], Speed: 6.123 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 9399], Speed: 5.550 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.232,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 9499], Speed: 5.929 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 9599], Speed: 6.091 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 9699], Speed: 5.360 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 9799], Speed: 5.808 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 9899], Speed: 5.971 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 9999], Speed: 5.563 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 10099], Speed: 5.910 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 10199], Speed: 6.295 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 10299], Speed: 5.845 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 10399], Speed: 5.574 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.187,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 10499], Speed: 5.530 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 10599], Speed: 6.234 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 10699], Speed: 6.020 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.125,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.694 +[Epoch 20][Batch 10799], Speed: 6.097 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 10899], Speed: 5.386 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 10999], Speed: 5.838 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11099], Speed: 6.684 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11199], Speed: 5.487 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11299], Speed: 5.635 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11399], Speed: 5.628 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11499], Speed: 5.817 samples/sec, RPN_Conf=0.019,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11599], Speed: 6.098 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11699], Speed: 5.931 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11799], Speed: 5.787 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11899], Speed: 6.548 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 11999], Speed: 5.884 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 12099], Speed: 5.389 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 12199], Speed: 5.769 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 12299], Speed: 5.778 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.693 +[Epoch 20][Batch 12399], Speed: 6.249 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 12499], Speed: 5.707 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 12599], Speed: 5.910 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 12699], Speed: 5.671 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 12799], Speed: 5.730 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.124,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 12899], Speed: 5.570 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 12999], Speed: 5.699 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13099], Speed: 5.997 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13199], Speed: 5.598 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13299], Speed: 5.591 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13399], Speed: 6.115 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13499], Speed: 5.647 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13599], Speed: 6.076 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13699], Speed: 6.005 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13799], Speed: 5.237 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13899], Speed: 5.829 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.692 +[Epoch 20][Batch 13999], Speed: 5.991 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 20][Batch 14099], Speed: 5.362 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 20][Batch 14199], Speed: 5.790 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 20][Batch 14299], Speed: 5.588 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.231,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 20][Batch 14399], Speed: 5.551 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 20][Batch 14499], Speed: 5.549 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 20][Batch 14599], Speed: 5.762 samples/sec, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.186,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 20] Training cost: 19970.674, RPN_Conf=0.018,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.123,RCNN_SmoothL1=0.185 +[Epoch 20] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.458 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.668 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.500 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.304 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.495 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.580 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.356 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.574 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.606 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.447 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.642 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.743 +person=57.6 +bicycle=35.6 +car=47.0 +motorcycle=47.7 +airplane=67.6 +bus=68.2 +train=67.8 +truck=40.8 +boat=32.2 +traffic light=30.0 +fire hydrant=71.1 +stop sign=67.9 +parking meter=54.7 +bench=29.7 +bird=38.0 +cat=72.9 +dog=65.6 +horse=63.6 +sheep=55.3 +cow=59.0 +elephant=64.1 +bear=68.2 +zebra=68.2 +giraffe=67.6 +backpack=18.1 +umbrella=43.0 +handbag=19.0 +tie=42.1 +suitcase=42.7 +frisbee=70.1 +skis=27.2 +snowboard=46.0 +sports ball=45.9 +kite=40.3 +baseball bat=42.2 +baseball glove=43.3 +skateboard=58.3 +surfboard=42.1 +tennis racket=57.6 +bottle=43.7 +wine glass=41.1 +cup=47.6 +fork=45.6 +knife=27.9 +spoon=26.4 +bowl=44.4 +banana=27.5 +apple=23.2 +sandwich=37.1 +orange=31.4 +broccoli=25.8 +carrot=24.3 +hot dog=38.8 +pizza=56.6 +donut=51.1 +cake=42.9 +chair=34.2 +couch=42.7 +potted plant=32.0 +bed=43.1 +dining table=29.7 +toilet=61.7 +tv=58.6 +laptop=62.7 +mouse=62.0 +remote=39.9 +keyboard=51.3 +cell phone=39.7 +microwave=61.2 +oven=38.2 +toaster=39.1 +sink=42.2 +refrigerator=61.8 +book=19.6 +clock=54.1 +vase=42.8 +scissors=37.5 +teddy bear=51.6 +hair drier=7.9 +toothbrush=35.9 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=45.8 +[Epoch 20] mAP 45.8 higher than current best [38.7] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 20] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0020_45.8000.params +[Epoch 21][Batch 99], Speed: 6.652 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.109,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 21][Batch 199], Speed: 6.821 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.182,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 21][Batch 299], Speed: 5.921 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.114,RCNN_SmoothL1=0.182,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 21][Batch 399], Speed: 6.362 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.036,RCNN_CrossEntropy=0.116,RCNN_SmoothL1=0.185,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 21][Batch 499], Speed: 6.046 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.114,RCNN_SmoothL1=0.183,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 21][Batch 599], Speed: 6.192 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.114,RCNN_SmoothL1=0.183,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 21][Batch 699], Speed: 5.621 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.115,RCNN_SmoothL1=0.183,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 21][Batch 799], Speed: 5.802 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.114,RCNN_SmoothL1=0.182,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.691 +[Epoch 21][Batch 899], Speed: 6.052 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.114,RCNN_SmoothL1=0.182,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 999], Speed: 6.004 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.114,RCNN_SmoothL1=0.182,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1099], Speed: 5.815 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.114,RCNN_SmoothL1=0.181,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1199], Speed: 6.345 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.114,RCNN_SmoothL1=0.182,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1299], Speed: 5.284 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.181,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1399], Speed: 5.844 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.180,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1499], Speed: 6.116 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.180,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1599], Speed: 5.615 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.180,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1699], Speed: 5.850 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.180,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1799], Speed: 5.623 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1899], Speed: 5.910 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 1999], Speed: 5.786 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 2099], Speed: 5.832 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 2199], Speed: 5.831 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 2299], Speed: 5.909 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.690 +[Epoch 21][Batch 2399], Speed: 5.544 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 2499], Speed: 5.453 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 2599], Speed: 5.761 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 2699], Speed: 5.982 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 2799], Speed: 6.220 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 2899], Speed: 5.513 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 2999], Speed: 5.969 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3099], Speed: 5.637 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3199], Speed: 5.935 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3299], Speed: 5.514 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3399], Speed: 5.423 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3499], Speed: 6.167 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3599], Speed: 5.955 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.035,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3699], Speed: 5.029 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3799], Speed: 5.868 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.689 +[Epoch 21][Batch 3899], Speed: 5.659 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.113,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 3999], Speed: 5.913 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4099], Speed: 5.589 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4199], Speed: 5.281 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4299], Speed: 6.417 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.230,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4399], Speed: 5.987 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4499], Speed: 6.627 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4599], Speed: 6.076 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4699], Speed: 5.990 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4799], Speed: 5.825 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4899], Speed: 5.471 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 4999], Speed: 6.041 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 5099], Speed: 5.651 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 5199], Speed: 5.678 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 5299], Speed: 5.869 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.688 +[Epoch 21][Batch 5399], Speed: 5.799 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 5499], Speed: 6.544 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 5599], Speed: 6.089 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 5699], Speed: 5.581 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 5799], Speed: 6.127 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 5899], Speed: 6.102 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 5999], Speed: 5.165 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6099], Speed: 5.936 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6199], Speed: 6.471 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6299], Speed: 5.760 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6399], Speed: 5.946 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6499], Speed: 5.630 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6599], Speed: 6.011 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6699], Speed: 5.637 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6799], Speed: 5.761 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.687 +[Epoch 21][Batch 6899], Speed: 5.596 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 6999], Speed: 5.750 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7099], Speed: 5.990 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7199], Speed: 5.818 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7299], Speed: 6.146 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7399], Speed: 5.355 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7499], Speed: 6.111 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7599], Speed: 6.140 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7699], Speed: 6.336 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7799], Speed: 6.304 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7899], Speed: 6.224 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 7999], Speed: 5.512 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 8099], Speed: 5.247 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 8199], Speed: 5.773 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 8299], Speed: 6.305 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.686 +[Epoch 21][Batch 8399], Speed: 5.775 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.685 +[Epoch 21][Batch 8499], Speed: 6.129 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.685 +[Epoch 21][Batch 8599], Speed: 6.253 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.685 +[Epoch 21][Batch 8699], Speed: 5.264 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.685 +[Epoch 21][Batch 8799], Speed: 5.913 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.685 +[Epoch 21][Batch 8899], Speed: 6.017 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.685 +[Epoch 21][Batch 8999], Speed: 5.546 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.229,RCNNAcc=0.940,RCNNL1Loss=0.685 +[Epoch 21][Batch 9099], Speed: 5.798 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.940,RCNNL1Loss=0.685 +[Epoch 21][Batch 9199], Speed: 5.511 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.685 +[Epoch 21][Batch 9299], Speed: 5.800 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.685 +[Epoch 21][Batch 9399], Speed: 5.705 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.685 +[Epoch 21][Batch 9499], Speed: 5.721 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.685 +[Epoch 21][Batch 9599], Speed: 5.922 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.685 +[Epoch 21][Batch 9699], Speed: 5.867 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.685 +[Epoch 21][Batch 9799], Speed: 5.814 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.685 +[Epoch 21][Batch 9899], Speed: 5.854 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.179,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.685 +[Epoch 21][Batch 9999], Speed: 5.876 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10099], Speed: 6.526 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10199], Speed: 5.979 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10299], Speed: 5.959 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10399], Speed: 5.935 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10499], Speed: 5.443 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10599], Speed: 5.983 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10699], Speed: 6.050 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10799], Speed: 5.826 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10899], Speed: 5.715 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 10999], Speed: 5.778 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 11099], Speed: 5.314 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 11199], Speed: 5.455 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 11299], Speed: 5.204 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 11399], Speed: 5.887 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.684 +[Epoch 21][Batch 11499], Speed: 6.191 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 11599], Speed: 5.741 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 11699], Speed: 5.834 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 11799], Speed: 5.667 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 11899], Speed: 5.613 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 11999], Speed: 5.591 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12099], Speed: 6.182 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12199], Speed: 5.654 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12299], Speed: 6.331 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12399], Speed: 6.033 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12499], Speed: 5.588 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12599], Speed: 5.597 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12699], Speed: 5.297 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12799], Speed: 6.282 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12899], Speed: 5.637 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 12999], Speed: 5.637 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.683 +[Epoch 21][Batch 13099], Speed: 5.753 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13199], Speed: 5.874 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13299], Speed: 5.736 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13399], Speed: 6.093 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13499], Speed: 5.560 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13599], Speed: 5.892 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13699], Speed: 5.916 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13799], Speed: 6.397 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.228,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13899], Speed: 5.575 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 13999], Speed: 5.809 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 14099], Speed: 5.368 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 14199], Speed: 5.451 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 14299], Speed: 5.595 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 14399], Speed: 6.012 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 14499], Speed: 5.620 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.682 +[Epoch 21][Batch 14599], Speed: 5.637 samples/sec, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 21] Training cost: 20115.769, RPN_Conf=0.016,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.112,RCNN_SmoothL1=0.178 +[Epoch 21] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.462 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.675 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.500 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.301 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.497 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.584 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.359 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.575 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.607 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.439 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.638 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.745 +person=57.8 +bicycle=35.1 +car=48.3 +motorcycle=47.9 +airplane=68.5 +bus=68.5 +train=68.2 +truck=41.2 +boat=31.3 +traffic light=29.0 +fire hydrant=70.4 +stop sign=69.1 +parking meter=53.0 +bench=29.6 +bird=38.9 +cat=73.8 +dog=66.4 +horse=62.8 +sheep=56.0 +cow=61.3 +elephant=64.8 +bear=66.8 +zebra=68.6 +giraffe=67.7 +backpack=18.1 +umbrella=44.3 +handbag=19.8 +tie=40.9 +suitcase=45.2 +frisbee=70.8 +skis=27.3 +snowboard=47.9 +sports ball=47.0 +kite=38.4 +baseball bat=40.2 +baseball glove=44.3 +skateboard=59.7 +surfboard=42.4 +tennis racket=58.0 +bottle=44.4 +wine glass=42.2 +cup=48.4 +fork=46.8 +knife=27.1 +spoon=28.2 +bowl=45.4 +banana=29.0 +apple=23.8 +sandwich=38.2 +orange=31.1 +broccoli=23.8 +carrot=24.3 +hot dog=40.5 +pizza=55.9 +donut=50.0 +cake=41.5 +chair=34.9 +couch=41.2 +potted plant=32.5 +bed=41.4 +dining table=29.2 +toilet=63.0 +tv=59.0 +laptop=64.5 +mouse=63.5 +remote=40.5 +keyboard=52.0 +cell phone=40.0 +microwave=59.7 +oven=39.5 +toaster=41.9 +sink=43.1 +refrigerator=63.6 +book=20.1 +clock=52.3 +vase=41.9 +scissors=40.4 +teddy bear=52.4 +hair drier=10.0 +toothbrush=35.9 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=46.2 +[Epoch 21] mAP 46.2 higher than current best [45.8] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 21] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0021_46.2000.params +[Epoch 22][Batch 99], Speed: 6.464 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.172,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 199], Speed: 6.355 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.109,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 299], Speed: 6.186 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.173,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 399], Speed: 5.895 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.173,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 499], Speed: 5.669 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.173,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 599], Speed: 6.210 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.173,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 699], Speed: 5.925 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.173,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 799], Speed: 6.134 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.173,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 899], Speed: 5.980 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.173,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 999], Speed: 5.732 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.173,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 1099], Speed: 5.536 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 1199], Speed: 6.286 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 1299], Speed: 6.149 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.681 +[Epoch 22][Batch 1399], Speed: 6.139 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 1499], Speed: 5.927 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 1599], Speed: 6.158 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 1699], Speed: 5.890 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 1799], Speed: 5.564 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 1899], Speed: 5.866 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 1999], Speed: 6.036 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2099], Speed: 5.353 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2199], Speed: 5.916 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2299], Speed: 5.575 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2399], Speed: 6.385 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2499], Speed: 5.684 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2599], Speed: 5.977 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2699], Speed: 5.577 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2799], Speed: 6.062 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.680 +[Epoch 22][Batch 2899], Speed: 6.166 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 2999], Speed: 6.237 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3099], Speed: 6.179 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3199], Speed: 5.641 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3299], Speed: 6.072 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3399], Speed: 5.988 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3499], Speed: 5.647 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3599], Speed: 6.126 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3699], Speed: 5.632 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3799], Speed: 6.181 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.227,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3899], Speed: 6.139 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 3999], Speed: 5.755 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 4099], Speed: 5.995 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 4199], Speed: 5.850 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 4299], Speed: 5.705 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.679 +[Epoch 22][Batch 4399], Speed: 5.927 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 4499], Speed: 5.708 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 4599], Speed: 5.571 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 4699], Speed: 5.776 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 4799], Speed: 5.710 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 4899], Speed: 5.778 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 4999], Speed: 5.712 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5099], Speed: 5.628 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5199], Speed: 5.510 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5299], Speed: 5.629 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5399], Speed: 6.069 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5499], Speed: 5.857 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.107,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5599], Speed: 5.871 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5699], Speed: 5.971 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5799], Speed: 5.731 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.678 +[Epoch 22][Batch 5899], Speed: 5.588 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 5999], Speed: 6.106 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.175,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6099], Speed: 5.843 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6199], Speed: 5.653 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6299], Speed: 5.828 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6399], Speed: 5.716 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6499], Speed: 6.081 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6599], Speed: 6.112 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6699], Speed: 5.985 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6799], Speed: 5.719 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6899], Speed: 6.110 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 6999], Speed: 5.612 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 7099], Speed: 5.781 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 7199], Speed: 5.341 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 7299], Speed: 5.696 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.677 +[Epoch 22][Batch 7399], Speed: 5.573 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 7499], Speed: 6.131 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 7599], Speed: 5.701 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 7699], Speed: 6.040 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 7799], Speed: 6.012 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 7899], Speed: 6.113 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 7999], Speed: 5.996 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8099], Speed: 5.979 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8199], Speed: 6.210 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8299], Speed: 6.364 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8399], Speed: 5.753 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8499], Speed: 6.252 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8599], Speed: 5.450 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8699], Speed: 5.722 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.226,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8799], Speed: 5.880 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.989,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8899], Speed: 6.230 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.676 +[Epoch 22][Batch 8999], Speed: 5.578 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9099], Speed: 6.347 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9199], Speed: 5.593 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9299], Speed: 5.716 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9399], Speed: 6.265 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9499], Speed: 5.957 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9599], Speed: 6.083 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9699], Speed: 6.084 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9799], Speed: 6.235 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9899], Speed: 6.082 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 9999], Speed: 6.195 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 10099], Speed: 5.936 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 10199], Speed: 5.850 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 10299], Speed: 5.822 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 10399], Speed: 6.303 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.675 +[Epoch 22][Batch 10499], Speed: 5.932 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 10599], Speed: 5.907 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 10699], Speed: 5.978 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 10799], Speed: 5.850 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 10899], Speed: 5.582 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 10999], Speed: 6.695 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11099], Speed: 5.323 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11199], Speed: 5.998 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11299], Speed: 5.679 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11399], Speed: 5.879 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11499], Speed: 5.696 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11599], Speed: 6.786 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11699], Speed: 6.156 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11799], Speed: 6.790 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11899], Speed: 6.114 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.674 +[Epoch 22][Batch 11999], Speed: 6.466 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.673 +[Epoch 22][Batch 12099], Speed: 5.550 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.941,RCNNL1Loss=0.673 +[Epoch 22][Batch 12199], Speed: 6.396 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 12299], Speed: 5.777 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 12399], Speed: 5.588 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 12499], Speed: 6.228 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 12599], Speed: 6.427 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 12699], Speed: 5.972 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 12799], Speed: 6.470 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 12899], Speed: 5.817 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 12999], Speed: 5.475 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 13099], Speed: 4.957 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 13199], Speed: 6.124 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 13299], Speed: 5.597 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 13399], Speed: 6.396 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 13499], Speed: 5.644 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.673 +[Epoch 22][Batch 13599], Speed: 5.625 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.225,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 13699], Speed: 5.314 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 13799], Speed: 6.046 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 13899], Speed: 5.834 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 13999], Speed: 6.000 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 14099], Speed: 5.685 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 14199], Speed: 5.484 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 14299], Speed: 5.868 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 14399], Speed: 5.647 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 14499], Speed: 5.781 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22][Batch 14599], Speed: 5.248 samples/sec, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 22] Training cost: 19899.348, RPN_Conf=0.015,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.106,RCNN_SmoothL1=0.174 +[Epoch 22] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.461 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.673 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.501 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.302 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.499 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.587 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.358 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.575 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.607 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.437 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.640 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.735 +person=58.0 +bicycle=35.1 +car=48.4 +motorcycle=47.6 +airplane=68.8 +bus=68.9 +train=69.1 +truck=40.3 +boat=31.0 +traffic light=29.7 +fire hydrant=70.5 +stop sign=67.1 +parking meter=53.1 +bench=29.9 +bird=38.5 +cat=73.3 +dog=66.6 +horse=64.7 +sheep=56.4 +cow=59.1 +elephant=64.9 +bear=66.5 +zebra=68.1 +giraffe=65.6 +backpack=19.4 +umbrella=43.7 +handbag=20.1 +tie=40.9 +suitcase=44.0 +frisbee=70.2 +skis=27.7 +snowboard=49.3 +sports ball=46.2 +kite=41.3 +baseball bat=39.6 +baseball glove=43.8 +skateboard=57.8 +surfboard=43.4 +tennis racket=56.5 +bottle=43.5 +wine glass=42.7 +cup=48.2 +fork=46.4 +knife=28.8 +spoon=27.2 +bowl=44.9 +banana=28.5 +apple=23.7 +sandwich=37.8 +orange=32.1 +broccoli=22.2 +carrot=24.3 +hot dog=42.5 +pizza=56.9 +donut=49.4 +cake=42.0 +chair=34.7 +couch=44.6 +potted plant=32.3 +bed=42.3 +dining table=30.3 +toilet=62.5 +tv=59.2 +laptop=63.5 +mouse=62.7 +remote=42.2 +keyboard=52.4 +cell phone=40.1 +microwave=63.8 +oven=39.7 +toaster=32.5 +sink=40.9 +refrigerator=64.1 +book=19.7 +clock=52.9 +vase=42.5 +scissors=39.5 +teddy bear=52.9 +hair drier=9.2 +toothbrush=35.3 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=46.1 +[Epoch 22] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0022_46.1000.params +[Epoch 23][Batch 99], Speed: 6.378 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.100,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 23][Batch 199], Speed: 6.415 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.103,RCNN_SmoothL1=0.172,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 23][Batch 299], Speed: 5.666 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.104,RCNN_SmoothL1=0.173,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 23][Batch 399], Speed: 5.498 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.103,RCNN_SmoothL1=0.172,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.672 +[Epoch 23][Batch 499], Speed: 5.434 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.103,RCNN_SmoothL1=0.172,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 599], Speed: 5.964 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.103,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 699], Speed: 6.305 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.103,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 799], Speed: 6.062 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 899], Speed: 5.856 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 999], Speed: 6.453 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1099], Speed: 6.050 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1199], Speed: 5.714 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.168,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1299], Speed: 6.020 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.168,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1399], Speed: 5.462 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.168,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1499], Speed: 5.670 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.100,RCNN_SmoothL1=0.168,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1599], Speed: 5.974 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.168,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1699], Speed: 5.932 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.168,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1799], Speed: 5.604 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.168,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1899], Speed: 5.736 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.671 +[Epoch 23][Batch 1999], Speed: 5.548 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2099], Speed: 5.725 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2199], Speed: 5.514 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2299], Speed: 6.178 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2399], Speed: 5.908 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2499], Speed: 5.592 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2599], Speed: 6.239 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2699], Speed: 6.485 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.169,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2799], Speed: 6.184 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2899], Speed: 6.229 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 2999], Speed: 5.943 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 3099], Speed: 6.265 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 3199], Speed: 6.064 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 3299], Speed: 5.813 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 3399], Speed: 5.647 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.670 +[Epoch 23][Batch 3499], Speed: 5.659 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 3599], Speed: 5.974 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 3699], Speed: 5.796 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 3799], Speed: 5.451 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.224,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 3899], Speed: 6.135 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 3999], Speed: 5.976 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4099], Speed: 5.975 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4199], Speed: 6.191 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4299], Speed: 5.776 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4399], Speed: 5.858 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4499], Speed: 5.356 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4599], Speed: 6.403 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4699], Speed: 5.358 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4799], Speed: 6.060 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4899], Speed: 6.081 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.669 +[Epoch 23][Batch 4999], Speed: 5.893 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5099], Speed: 6.098 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5199], Speed: 5.607 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.101,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5299], Speed: 6.079 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5399], Speed: 6.253 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5499], Speed: 5.995 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5599], Speed: 6.061 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5699], Speed: 5.867 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5799], Speed: 6.152 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5899], Speed: 5.736 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 5999], Speed: 5.834 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 6099], Speed: 5.720 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 6199], Speed: 5.946 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 6299], Speed: 6.106 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 6399], Speed: 6.103 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.668 +[Epoch 23][Batch 6499], Speed: 6.173 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 6599], Speed: 6.118 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 6699], Speed: 6.279 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 6799], Speed: 5.800 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 6899], Speed: 5.509 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 6999], Speed: 5.481 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7099], Speed: 6.131 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7199], Speed: 6.079 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7299], Speed: 5.927 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7399], Speed: 5.597 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7499], Speed: 6.168 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7599], Speed: 5.706 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7699], Speed: 5.321 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7799], Speed: 6.090 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7899], Speed: 5.617 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 7999], Speed: 6.107 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.667 +[Epoch 23][Batch 8099], Speed: 5.711 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8199], Speed: 5.613 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8299], Speed: 6.358 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8399], Speed: 5.655 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8499], Speed: 5.797 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8599], Speed: 5.687 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8699], Speed: 5.749 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8799], Speed: 6.221 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.223,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8899], Speed: 6.150 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 8999], Speed: 6.206 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 9099], Speed: 6.300 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 9199], Speed: 5.821 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 9299], Speed: 5.670 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 9399], Speed: 5.835 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 9499], Speed: 5.783 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.666 +[Epoch 23][Batch 9599], Speed: 6.110 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 9699], Speed: 5.838 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 9799], Speed: 5.932 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 9899], Speed: 5.990 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 9999], Speed: 6.455 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10099], Speed: 5.793 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10199], Speed: 5.709 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10299], Speed: 5.855 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10399], Speed: 6.324 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10499], Speed: 5.849 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10599], Speed: 6.286 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10699], Speed: 5.565 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10799], Speed: 5.634 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10899], Speed: 5.853 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 10999], Speed: 6.199 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 11099], Speed: 5.870 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.665 +[Epoch 23][Batch 11199], Speed: 5.519 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 11299], Speed: 5.819 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 11399], Speed: 5.927 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 11499], Speed: 6.188 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 11599], Speed: 5.960 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 11699], Speed: 5.935 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 11799], Speed: 5.385 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 11899], Speed: 5.678 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 11999], Speed: 5.717 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 12099], Speed: 5.947 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 12199], Speed: 6.452 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 12299], Speed: 5.408 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 12399], Speed: 6.288 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 12499], Speed: 6.005 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 12599], Speed: 5.464 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 12699], Speed: 5.634 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.664 +[Epoch 23][Batch 12799], Speed: 5.718 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 12899], Speed: 5.981 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 12999], Speed: 5.964 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13099], Speed: 5.231 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13199], Speed: 5.902 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13299], Speed: 5.813 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13399], Speed: 5.288 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13499], Speed: 5.418 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13599], Speed: 6.448 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13699], Speed: 5.754 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13799], Speed: 5.584 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13899], Speed: 5.551 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.222,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 13999], Speed: 6.405 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 14099], Speed: 5.721 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 14199], Speed: 6.056 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 14299], Speed: 5.493 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.663 +[Epoch 23][Batch 14399], Speed: 5.904 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 23][Batch 14499], Speed: 5.975 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 23][Batch 14599], Speed: 5.426 samples/sec, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 23] Training cost: 19963.261, RPN_Conf=0.014,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.102,RCNN_SmoothL1=0.170 +[Epoch 23] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.460 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.673 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.504 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.305 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.497 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.585 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.357 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.570 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.601 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.431 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.633 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.738 +person=57.6 +bicycle=34.4 +car=48.7 +motorcycle=48.4 +airplane=69.0 +bus=68.9 +train=69.3 +truck=43.3 +boat=30.5 +traffic light=29.7 +fire hydrant=71.1 +stop sign=68.3 +parking meter=52.2 +bench=30.0 +bird=39.3 +cat=72.4 +dog=66.8 +horse=63.7 +sheep=56.2 +cow=60.0 +elephant=65.0 +bear=67.4 +zebra=67.1 +giraffe=68.3 +backpack=19.7 +umbrella=43.6 +handbag=19.5 +tie=40.7 +suitcase=39.0 +frisbee=69.3 +skis=27.6 +snowboard=48.7 +sports ball=45.1 +kite=40.2 +baseball bat=39.0 +baseball glove=43.6 +skateboard=58.1 +surfboard=42.9 +tennis racket=57.3 +bottle=43.1 +wine glass=42.2 +cup=48.0 +fork=45.6 +knife=29.2 +spoon=26.5 +bowl=44.5 +banana=28.9 +apple=23.4 +sandwich=36.9 +orange=31.5 +broccoli=24.0 +carrot=23.8 +hot dog=44.0 +pizza=55.4 +donut=48.9 +cake=41.0 +chair=34.5 +couch=42.5 +potted plant=32.3 +bed=42.3 +dining table=31.1 +toilet=63.3 +tv=58.9 +laptop=64.7 +mouse=62.0 +remote=40.0 +keyboard=52.9 +cell phone=40.8 +microwave=63.5 +oven=38.4 +toaster=41.0 +sink=41.2 +refrigerator=63.2 +book=19.4 +clock=52.2 +vase=43.0 +scissors=35.8 +teddy bear=51.3 +hair drier=8.8 +toothbrush=37.7 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=46.0 +[Epoch 23] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0023_46.0000.params +[Epoch 24] Set learning rate to 0.0001 +[Epoch 24][Batch 99], Speed: 6.131 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.098,RCNN_SmoothL1=0.173,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 24][Batch 199], Speed: 6.181 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.034,RCNN_CrossEntropy=0.098,RCNN_SmoothL1=0.172,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 24][Batch 299], Speed: 6.281 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.168,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 24][Batch 399], Speed: 6.052 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.166,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 24][Batch 499], Speed: 6.136 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 24][Batch 599], Speed: 5.716 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.942,RCNNL1Loss=0.662 +[Epoch 24][Batch 699], Speed: 5.796 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.662 +[Epoch 24][Batch 799], Speed: 5.882 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.662 +[Epoch 24][Batch 899], Speed: 5.944 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.662 +[Epoch 24][Batch 999], Speed: 6.098 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.662 +[Epoch 24][Batch 1099], Speed: 5.720 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.662 +[Epoch 24][Batch 1199], Speed: 6.423 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.662 +[Epoch 24][Batch 1299], Speed: 5.912 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 1399], Speed: 5.886 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 1499], Speed: 6.071 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 1599], Speed: 5.951 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 1699], Speed: 5.253 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 1799], Speed: 6.002 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 1899], Speed: 6.098 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 1999], Speed: 5.896 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 2099], Speed: 5.980 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 2199], Speed: 6.469 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 2299], Speed: 6.028 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 2399], Speed: 5.828 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 2499], Speed: 5.737 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 2599], Speed: 5.650 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.661 +[Epoch 24][Batch 2699], Speed: 5.654 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 2799], Speed: 6.498 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 2899], Speed: 6.161 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 2999], Speed: 6.128 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3099], Speed: 5.988 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3199], Speed: 5.944 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3299], Speed: 5.653 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3399], Speed: 5.293 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3499], Speed: 5.596 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3599], Speed: 5.588 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3699], Speed: 6.215 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3799], Speed: 6.034 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3899], Speed: 6.286 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 3999], Speed: 5.680 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 4099], Speed: 5.749 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.221,RCNNAcc=0.943,RCNNL1Loss=0.660 +[Epoch 24][Batch 4199], Speed: 5.819 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 4299], Speed: 5.978 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 4399], Speed: 6.335 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 4499], Speed: 5.608 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 4599], Speed: 6.009 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 4699], Speed: 5.790 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 4799], Speed: 5.555 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 4899], Speed: 5.703 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 4999], Speed: 5.540 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 5099], Speed: 5.769 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 5199], Speed: 5.401 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 5299], Speed: 6.244 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 5399], Speed: 6.071 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 5499], Speed: 5.431 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 5599], Speed: 5.193 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.659 +[Epoch 24][Batch 5699], Speed: 5.568 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 5799], Speed: 5.942 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 5899], Speed: 5.761 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 5999], Speed: 6.166 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6099], Speed: 6.271 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6199], Speed: 5.762 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6299], Speed: 5.634 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6399], Speed: 5.955 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6499], Speed: 5.790 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6599], Speed: 5.750 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6699], Speed: 6.112 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6799], Speed: 5.615 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6899], Speed: 6.163 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 6999], Speed: 5.329 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 7099], Speed: 6.137 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.658 +[Epoch 24][Batch 7199], Speed: 6.171 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 7299], Speed: 6.098 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 7399], Speed: 5.932 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 7499], Speed: 5.963 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 7599], Speed: 5.919 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 7699], Speed: 5.875 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 7799], Speed: 6.284 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 7899], Speed: 6.161 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 7999], Speed: 5.674 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 8099], Speed: 5.919 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 8199], Speed: 6.332 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 8299], Speed: 6.348 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 8399], Speed: 6.132 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 8499], Speed: 5.503 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 8599], Speed: 5.975 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.657 +[Epoch 24][Batch 8699], Speed: 5.636 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 8799], Speed: 5.642 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 8899], Speed: 6.123 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 8999], Speed: 6.004 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.220,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9099], Speed: 6.060 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9199], Speed: 5.838 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9299], Speed: 6.055 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9399], Speed: 5.520 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9499], Speed: 5.482 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9599], Speed: 5.392 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9699], Speed: 5.130 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9799], Speed: 5.869 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9899], Speed: 6.052 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 9999], Speed: 6.181 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 10099], Speed: 5.826 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.656 +[Epoch 24][Batch 10199], Speed: 5.926 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 10299], Speed: 6.218 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 10399], Speed: 5.903 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 10499], Speed: 6.109 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 10599], Speed: 5.956 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 10699], Speed: 5.572 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 10799], Speed: 5.955 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 10899], Speed: 5.461 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 10999], Speed: 6.145 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 11099], Speed: 5.913 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 11199], Speed: 5.643 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 11299], Speed: 5.659 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 11399], Speed: 5.801 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 11499], Speed: 5.760 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 11599], Speed: 5.903 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 11699], Speed: 5.796 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.655 +[Epoch 24][Batch 11799], Speed: 5.505 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 11899], Speed: 5.887 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 11999], Speed: 6.120 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12099], Speed: 6.072 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12199], Speed: 5.374 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12299], Speed: 6.324 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12399], Speed: 5.517 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12499], Speed: 6.015 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12599], Speed: 5.927 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12699], Speed: 5.848 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12799], Speed: 6.442 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12899], Speed: 6.027 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 12999], Speed: 5.960 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 13099], Speed: 5.888 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 13199], Speed: 5.657 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 13299], Speed: 6.525 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.654 +[Epoch 24][Batch 13399], Speed: 5.558 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 13499], Speed: 6.055 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 13599], Speed: 5.583 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 13699], Speed: 6.337 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 13799], Speed: 5.450 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 13899], Speed: 5.953 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.096,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 13999], Speed: 6.189 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 14099], Speed: 6.090 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.219,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 14199], Speed: 5.843 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 14299], Speed: 6.385 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 14399], Speed: 5.908 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 14499], Speed: 6.042 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24][Batch 14599], Speed: 6.129 samples/sec, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 24] Training cost: 19922.120, RPN_Conf=0.013,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165 +[Epoch 24] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.465 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.675 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.507 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.306 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.499 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.594 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.359 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.573 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.604 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.435 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.635 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.741 +person=58.0 +bicycle=34.8 +car=48.5 +motorcycle=49.8 +airplane=69.6 +bus=70.3 +train=69.6 +truck=42.7 +boat=31.0 +traffic light=29.6 +fire hydrant=71.4 +stop sign=68.3 +parking meter=53.4 +bench=30.8 +bird=39.6 +cat=73.7 +dog=67.5 +horse=63.6 +sheep=57.0 +cow=59.7 +elephant=66.1 +bear=67.5 +zebra=68.8 +giraffe=69.5 +backpack=20.1 +umbrella=44.5 +handbag=20.4 +tie=41.7 +suitcase=41.6 +frisbee=69.9 +skis=28.3 +snowboard=50.0 +sports ball=46.1 +kite=42.0 +baseball bat=42.0 +baseball glove=43.9 +skateboard=59.3 +surfboard=43.6 +tennis racket=57.2 +bottle=43.5 +wine glass=42.4 +cup=48.7 +fork=46.5 +knife=28.8 +spoon=26.3 +bowl=45.0 +banana=28.7 +apple=24.6 +sandwich=36.5 +orange=31.2 +broccoli=25.0 +carrot=24.3 +hot dog=45.2 +pizza=56.4 +donut=49.0 +cake=41.7 +chair=34.6 +couch=44.7 +potted plant=32.3 +bed=43.7 +dining table=31.0 +toilet=63.4 +tv=59.7 +laptop=64.8 +mouse=61.6 +remote=42.6 +keyboard=52.5 +cell phone=41.5 +microwave=65.5 +oven=39.1 +toaster=35.8 +sink=43.6 +refrigerator=62.2 +book=19.9 +clock=53.6 +vase=43.0 +scissors=37.7 +teddy bear=51.6 +hair drier=6.6 +toothbrush=34.1 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=46.5 +[Epoch 24] mAP 46.5 higher than current best [46.2] saving to faster_rcnn_fpn_syncbn_resnest269_coco_best.params +[Epoch 24] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0024_46.5000.params +[Epoch 25][Batch 99], Speed: 6.227 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.033,RCNN_CrossEntropy=0.097,RCNN_SmoothL1=0.171,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 25][Batch 199], Speed: 6.156 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.165,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.653 +[Epoch 25][Batch 299], Speed: 6.077 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 399], Speed: 5.680 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.093,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 499], Speed: 6.055 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.093,RCNN_SmoothL1=0.162,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 599], Speed: 5.248 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 699], Speed: 6.547 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.093,RCNN_SmoothL1=0.162,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 799], Speed: 6.064 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 899], Speed: 6.124 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.093,RCNN_SmoothL1=0.162,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 999], Speed: 5.321 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.162,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 1099], Speed: 6.251 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.162,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 1199], Speed: 6.175 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.162,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 1299], Speed: 5.543 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 1399], Speed: 5.572 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 1499], Speed: 6.408 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 1599], Speed: 5.697 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 1699], Speed: 6.166 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.652 +[Epoch 25][Batch 1799], Speed: 5.985 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 1899], Speed: 6.081 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 1999], Speed: 5.643 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2099], Speed: 6.071 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2199], Speed: 6.569 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2299], Speed: 6.138 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2399], Speed: 5.722 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2499], Speed: 6.069 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2599], Speed: 5.847 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2699], Speed: 6.894 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2799], Speed: 5.724 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2899], Speed: 5.946 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 2999], Speed: 5.580 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 3099], Speed: 6.244 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 3199], Speed: 6.071 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 3299], Speed: 5.727 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.943,RCNNL1Loss=0.651 +[Epoch 25][Batch 3399], Speed: 5.566 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 3499], Speed: 5.978 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 3599], Speed: 5.268 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 3699], Speed: 5.652 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 3799], Speed: 5.771 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 3899], Speed: 5.657 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 3999], Speed: 5.695 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4099], Speed: 6.177 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4199], Speed: 5.960 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4299], Speed: 6.034 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4399], Speed: 5.732 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4499], Speed: 6.111 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4599], Speed: 5.686 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.218,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4699], Speed: 6.432 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4799], Speed: 5.982 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.650 +[Epoch 25][Batch 4899], Speed: 6.077 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 4999], Speed: 5.533 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5099], Speed: 6.326 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5199], Speed: 5.344 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5299], Speed: 5.822 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5399], Speed: 5.407 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5499], Speed: 5.443 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5599], Speed: 5.905 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.163,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5699], Speed: 5.721 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5799], Speed: 5.397 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5899], Speed: 5.906 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 5999], Speed: 5.441 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 6099], Speed: 5.620 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 6199], Speed: 5.930 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 6299], Speed: 5.800 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.095,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 6399], Speed: 5.421 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.649 +[Epoch 25][Batch 6499], Speed: 5.474 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 6599], Speed: 5.507 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 6699], Speed: 6.328 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 6799], Speed: 6.045 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 6899], Speed: 5.585 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 6999], Speed: 5.426 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7099], Speed: 6.473 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7199], Speed: 5.757 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7299], Speed: 5.430 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7399], Speed: 6.291 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7499], Speed: 6.094 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7599], Speed: 6.068 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7699], Speed: 6.076 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7799], Speed: 5.609 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7899], Speed: 5.917 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 7999], Speed: 5.882 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 8099], Speed: 5.823 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.648 +[Epoch 25][Batch 8199], Speed: 5.732 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 8299], Speed: 5.939 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 8399], Speed: 5.990 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 8499], Speed: 5.677 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 8599], Speed: 5.536 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 8699], Speed: 6.006 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 8799], Speed: 5.957 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 8899], Speed: 5.782 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 8999], Speed: 6.701 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 9099], Speed: 5.907 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 9199], Speed: 5.716 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 9299], Speed: 5.678 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 9399], Speed: 5.255 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 9499], Speed: 6.092 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 9599], Speed: 5.935 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 9699], Speed: 5.913 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.647 +[Epoch 25][Batch 9799], Speed: 6.032 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 9899], Speed: 6.066 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 9999], Speed: 6.013 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.217,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10099], Speed: 6.138 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10199], Speed: 5.996 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10299], Speed: 6.182 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10399], Speed: 5.732 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10499], Speed: 6.165 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10599], Speed: 6.027 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10699], Speed: 6.200 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10799], Speed: 5.738 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10899], Speed: 6.082 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 10999], Speed: 6.392 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 11099], Speed: 5.938 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 11199], Speed: 5.800 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 11299], Speed: 5.749 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 11399], Speed: 5.614 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.646 +[Epoch 25][Batch 11499], Speed: 5.823 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 11599], Speed: 6.151 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 11699], Speed: 5.947 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 11799], Speed: 5.705 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 11899], Speed: 6.008 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 11999], Speed: 5.930 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12099], Speed: 5.658 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12199], Speed: 6.444 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12299], Speed: 5.787 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12399], Speed: 6.017 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12499], Speed: 5.710 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12599], Speed: 5.670 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12699], Speed: 5.763 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12799], Speed: 5.694 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12899], Speed: 5.592 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 12999], Speed: 5.738 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.645 +[Epoch 25][Batch 13099], Speed: 5.981 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13199], Speed: 5.760 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13299], Speed: 5.544 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13399], Speed: 5.772 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13499], Speed: 6.406 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13599], Speed: 5.876 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13699], Speed: 5.631 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13799], Speed: 5.683 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13899], Speed: 6.197 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 13999], Speed: 5.212 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 14099], Speed: 5.784 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 14199], Speed: 5.437 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 14299], Speed: 5.820 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 14399], Speed: 6.333 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 14499], Speed: 5.421 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25][Batch 14599], Speed: 5.363 samples/sec, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164,RPNAcc=0.990,RPNL1Loss=0.216,RCNNAcc=0.944,RCNNL1Loss=0.644 +[Epoch 25] Training cost: 20028.291, RPN_Conf=0.012,RPN_SmoothL1=0.032,RCNN_CrossEntropy=0.094,RCNN_SmoothL1=0.164 +[Epoch 25] Validation: +~~~~ Summary metrics ~~~~ +=Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.464 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.674 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.508 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.306 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.499 + Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.594 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.359 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.573 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.603 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.433 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.634 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.740 +person=58.1 +bicycle=34.6 +car=48.6 +motorcycle=48.7 +airplane=68.8 +bus=69.6 +train=69.1 +truck=42.4 +boat=31.1 +traffic light=29.3 +fire hydrant=71.1 +stop sign=69.0 +parking meter=53.7 +bench=30.5 +bird=38.8 +cat=74.5 +dog=67.2 +horse=64.6 +sheep=57.6 +cow=60.1 +elephant=67.2 +bear=69.7 +zebra=68.1 +giraffe=69.9 +backpack=19.3 +umbrella=44.4 +handbag=20.3 +tie=41.8 +suitcase=40.2 +frisbee=70.3 +skis=28.6 +snowboard=48.6 +sports ball=46.3 +kite=41.1 +baseball bat=42.9 +baseball glove=43.9 +skateboard=59.6 +surfboard=44.2 +tennis racket=57.6 +bottle=43.6 +wine glass=42.9 +cup=49.0 +fork=46.7 +knife=28.7 +spoon=26.7 +bowl=45.4 +banana=29.4 +apple=24.3 +sandwich=37.9 +orange=31.6 +broccoli=23.1 +carrot=24.7 +hot dog=44.8 +pizza=56.3 +donut=49.4 +cake=41.0 +chair=35.0 +couch=44.3 +potted plant=32.2 +bed=42.9 +dining table=30.5 +toilet=62.7 +tv=59.9 +laptop=64.7 +mouse=62.7 +remote=41.8 +keyboard=52.5 +cell phone=41.8 +microwave=64.2 +oven=38.3 +toaster=32.2 +sink=42.7 +refrigerator=62.1 +book=20.2 +clock=52.9 +vase=42.6 +scissors=36.6 +teddy bear=51.9 +hair drier=7.2 +toothbrush=35.4 +~~~~ MeanAP @ IoU=[0.50,0.95] ~~~~ +=46.4 +[Epoch 25] Saving parameters to faster_rcnn_fpn_syncbn_resnest269_coco_0025_46.4000.params