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20B.yml
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20B.yml
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# DISCLAIMER: This is the configuration file for the GPT-NeoX-20B model as it was trained on 96x 40GB A100
# GPUs. Depending on your system configuration, you may need to change some parameters in order to fit
# the model in memory.
{
# Tokenizer / checkpoint settings - you will need to change these to the location you have them saved in
"vocab_file": "./20B_checkpoints/20B_tokenizer.json",
"save": "./20B_checkpoints",
"load": "./20B_checkpoints",
# If finetuning, edit the following to the location of your finetuning dataset:
"data_path": "./data/pile_20B_tokenizer/pile_20B_tokenizer_text_document",
# parallelism settings ( you will want to change these based on your cluster setup, ideally scheduling pipeline stages
# across the node boundaries )
"pipe_parallel_size": 4,
"model_parallel_size": 2,
# model settings
"num_layers": 44,
"hidden_size": 6144,
"num_attention_heads": 64,
"seq_length": 2048,
"max_position_embeddings": 2048,
"norm": "layernorm",
"pos_emb": "rotary",
"rotary_pct": 0.25,
"no_weight_tying": true,
"gpt_j_residual": true,
"output_layer_parallelism": "column",
"scaled_upper_triang_masked_softmax_fusion": true,
"bias_gelu_fusion": true,
# init methods
"init_method": "small_init",
"output_layer_init_method": "wang_init",
# optimizer settings
"optimizer": {
"type": "Adam",
"params": {
"lr": 0.97e-4,
"betas": [0.9, 0.95],
"eps": 1.0e-8,
}
},
"min_lr": 0.97e-5,
# for all zero_optimization options, see https://www.deepspeed.ai/docs/config-json/#zero-optimizations-for-fp16-training
"zero_optimization": {
"stage": 1,
"allgather_partitions": True,
"allgather_bucket_size": 1260000000,
"overlap_comm": True,
"reduce_scatter": True,
"reduce_bucket_size": 1260000000,
"contiguous_gradients": True,
},
# batch / data settings (assuming 96 GPUs)
"train_micro_batch_size_per_gpu": 4,
"gradient_accumulation_steps": 32,
"data_impl": "mmap",
"split": "995,4,1",
# activation checkpointing
"checkpoint_activations": true,
"checkpoint_num_layers": 1,
"partition_activations": false,
"synchronize_each_layer": true,
# regularization
"gradient_clipping": 1.0,
"weight_decay": 0.01,
"hidden_dropout": 0,
"attention_dropout": 0,
# precision settings
"fp16": {
"fp16": true,
"enabled": true,
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 12,
"hysteresis": 2,
"min_loss_scale": 1
},
# misc. training settings
"train_iters": 150000,
"lr_decay_iters": 150000,
"distributed_backend": "nccl",
"lr_decay_style": "cosine",
"warmup": 0.01,
"checkpoint_factor": 500, # this variable previously called `save-interval`
"eval_interval": 1000,
"eval_iters": 10,
# logging
"log_interval": 2,
"steps_per_print": 2,
"wall_clock_breakdown": false,
### NEW DATA: ####
"tokenizer_type": "HFTokenizer",
"tensorboard-dir": "./tensorboard",
"log_dir": "./logs",
}