[DOC] Add ernie-1.0-base-zh-cw benchmark results. (#3248)

PaddlePaddle · Sep 15, 2022 · 37a6860 · 37a6860
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diff --git a/examples/benchmark/clue/README.md b/examples/benchmark/clue/README.md
@@ -70,7 +70,7 @@
         </tr>        <tr>
             <td rowspan=3 align=center> 24L1024H </td>
             <td style="text-align:center">
-                <span style="font-size:18px">ERNIE 1.0-Large-zh-CW</span>
+                <span style="font-size:18px">ERNIE 1.0-Large-zh-cw</span>
             </td>
             <td style="text-align:center">
                 <span style="font-size:18px"><b>79.03</b></span>
@@ -222,7 +222,7 @@
             </td>
         </tr>
         <tr>
-            <td rowspan=8 align=center> 12L768H </td>
+            <td rowspan=9 align=center> 12L768H </td>
             <td style="text-align:center">
                 <span style="font-size:18px">
                     <a href="https://bj.bcebos.com/paddlenlp/models/transformers/ernie_3.0/ernie_3.0_base_zh.pdparams">
@@ -264,6 +264,44 @@
                 <span style="font-size:18px"><b>77.88</b></span>
             </td>
         </tr>
+        <tr>
+            <td style="text-align:center">
+                <span style="font-size:18px">ERNIE 1.0-Base-zh-cw</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">76.47</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">76.07</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">57.86</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">59.91</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">83.41</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">79.58</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">89.91</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">83.42</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">72.88/90.78</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">84.68</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">76.98</span>
+            </td>
+        </tr>
         <tr>
             <td style="text-align:center">
                 <span style="font-size:18px">ERNIE-Gram-zh</span>
@@ -1196,6 +1234,7 @@ AFQMC（语义相似度）、TNEWS（文本分类）、IFLYTEK（长文本分类
 | ERNIE 2.0-Large-zh               | 1e-5,32 | 3e-5,64 | 3e-5,32 | 2e-5,32  | 1e-5,16  | 3e-5,32     | 1e-5,64 | 2e-5,24  | 2e-5,24 | 3e-5,32       |
 | HFL/RoBERTa-wwm-ext-large        | 1e-5,32 | 3e-5,32 | 2e-5,32 | 1e-5,16  | 1e-5,16  | 2e-5,16     | 2e-5,16 | 3e-5,32  | 1e-5,24 | 2e-5,24       |
 | ERNIE 3.0-Base-zh                | 3e-5,16 | 3e-5,32 | 5e-5,32 | 3e-5,32  | 2e-5,64  | 2e-5,16     | 2e-5,32 | 2e-5,24  | 3e-5,24 | 3e-5,32       |
+| ERNIE 1.0-Base-zh-cw             | 2e-5,16 | 3e-5,32 | 5e-5,16 | 2e-5,16  | 3e-5,32  | 2e-5,16     | 2e-5,32 | 3e-5,24  | 2e-5,32 | 3e-5,24     |
 | ERNIE-Gram-zh                    | 1e-5,16 | 5e-5,16 | 5e-5,16 | 2e-5,32  | 2e-5,64  | 3e-5,16     | 3e-5,64 | 3e-5,32  | 2e-5,24 | 2e-5,24       |
 | ERNIE 2.0-Base-zh                | 3e-5,64 | 3e-5,64 | 5e-5,16 | 5e-5,64  | 5e-5,32  | 5e-5,16     | 2e-5,16 | 2e-5,32  | 3e-5,24 | 3e-5,32       |
 | Langboat/Mengzi-Bert-Base        | 3e-5,32 | 5e-5,32 | 5e-5,16 | 2e-5,16  | 2e-5,16  | 3e-5,8      | 1e-5,16 | 3e-5,24  | 3e-5,24 | 2e-5,32       |

diff --git a/model_zoo/ernie-1.0/README.md b/model_zoo/ernie-1.0/README.md
@@ -484,24 +484,24 @@ python3 -u  -m paddle.distributed.launch \
 
     我们release了base、large两个模型。均取得了较好的预训练效果。
 
-    - **ERNIE 1.0-Base-zh-CW** 模型：
+    - **ERNIE 1.0-Base-zh-cw** 模型：
         - 使用CLUE，WuDao共计400GB的语料，batch_size 1024, 训练 400w step，即可训练得到`ernie-3.0-base-zh`类似的模型效果。相关模型参数，开源为`ernie-1.0-base-zh-cw`，用户加载即可使用。使用CLUE benchmark 对最优超参数进行GradSearch搜索：
 
 Model&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | Arch | CLUE AVG |  AFQMC | TNEWS | IFLYTEK | CMNLI | OCNLI | CLUE WSC2020 | CSL | CMRC | CHID | C3
 -- | -- | -- | -- | -- | -- | -- |  -- | -- | -- | -- | -- |  -- |
  Metrics |   |   | Acc | Acc | Acc | Acc | Acc | Acc | Acc | Exact/F1| Acc| Acc | Acc
-ERNIE 1.0-Base-zh-CW | 12L768H | <b>76.44</b> | 76.04 |    58.02 |    60.87 |    83.56 | 78.61 |    89.14 |    84.00 |  72.26/90.40 |    84.73 |    77.15 |
+ERNIE 1.0-Base-zh-cw | 12L768H | <b>76.47</b> | 76.07 |    57.86 |    59.91 |    83.41 | 79.91 |    89.91 |   <b>83.42</b> |  72.88/90.78 |    <b>84.68</b> |    76.98 |
 ERNIE 2.0-Base-zh | 12L768H | 74.95  | 76.25 |    58.53 |    61.72 |    83.07 |    78.81 |    84.21 |    82.77 | 68.22/88.71    | 82.78    | 73.19
 ERNIE 1.0-Base-zh | 12L768H | 74.17 | 74.84 |    58.91 |    62.25 |    81.68 |    76.58 |    85.20 |    82.77 | 67.32/87.83 | 82.47 | 69.68
 -
-    - **ERNIE 1.0-Large-zh-CW** 模型：
+    - **ERNIE 1.0-Large-zh-cw** 模型：
 
         - 除了base模型外，我们还训练了放出了large模型。此模型参数采用的是词表与ernie-1.0相同，因此命名为`ernie-1.0-large-zh-cw`。使用开源语料，batch_size 512, 训练 400w step，训练去除SOP任务，只保留MLM损失：
 
 Model&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;  | Arch | CLUE AVG |  AFQMC | TNEWS | IFLYTEK | CMNLI | OCNLI | CLUE WSC2020 | CSL | CMRC | CHID | C3
 -- | -- | -- | -- | -- | -- | -- |  -- | -- | -- | -- | -- |  -- |
 Metrics |   |   | Acc | Acc | Acc | Acc | Acc | Acc | Acc | Exact/F1 | Acc| Acc
-ERNIE 1.0-Large-zh-CW| 24L1024H | <b>79.03</b> | 75.97 |    59.65 |    62.91 |    85.09 |    81.73| 93.09 |    84.53 | 74.22/91.88 | 88.57 | 84.54
+ERNIE 1.0-Large-zh-cw | 24L1024H | <b>79.03</b> | 75.97 |    59.65 |    62.91 |    85.09 |    81.73| 93.09 |    84.53 | 74.22/91.88 | 88.57 | 84.54
 ERNIE 3.0-Xbase-zh| 20L1024H | 78.71 | 76.85 |    59.89 |    62.41 |    84.76 |    82.51 |    89.80 |    84.47 |    75.49/92.67 | 86.36 | 84.59
 RoBERTa-wwm-ext-large | 24L1024H | 76.61 |    76.00 |    59.33 |    62.02 |    83.88 |    78.81 |    90.79 |    83.67 |    70.58/89.82 |    85.72 |    75.26
 

diff --git a/model_zoo/ernie-1.0/pretraining_introduction.md b/model_zoo/ernie-1.0/pretraining_introduction.md
@@ -24,8 +24,8 @@ PaddleNLP致力于预训练开源工作，使用开源中文语料CLUE、WuDao
     - [3.4 训练数据流配置](#data_pipe)
     - [3.5 观察评估](#观察评估)
 - [4. 训练效果](#release_models)
-    - [4.1 ERNIE 1.0-Base-zh-CW 模型](#ernie-1.0-base-zh-cw)
-    - [4.2 ERNIE 1.0-Large-zh-CW 模型](#ernie-1.0-large-zh-cw)
+    - [4.1 ERNIE 1.0-Base-zh-cw 模型](#ernie-1.0-base-zh-cw)
+    - [4.2 ERNIE 1.0-Large-zh-cw 模型](#ernie-1.0-large-zh-cw)
 * [5. 参考](#references)
 
 全部流程介绍图如下：
@@ -577,28 +577,28 @@ python3 -u  -m paddle.distributed.launch \
 
 <a name="ernie-1.0-base-zh-cw"></a>
 
-### 4.1 ERNIE 1.0-Base-zh-CW 模型
+### 4.1 ERNIE 1.0-Base-zh-cw 模型
 
 使用CLUE，WuDao共计400GB的语料，batch_size 1024, 训练 400w step，即可训练得到`ernie-3.0-base-zh`类似的模型效果。相关模型参数，开源为`ernie-1.0-base-zh-cw`，用户加载即可使用。使用CLUE benchmark 对最优超参数进行GradSearch搜索：
 
 Model&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; | Arch | CLUE AVG |  AFQMC | TNEWS | IFLYTEK | CMNLI | OCNLI | CLUE WSC2020 | CSL | CMRC | CHID | C3
 -- | -- | -- | -- | -- | -- | -- |  -- | -- | -- | -- | -- |  -- |
  Metrics |   |   | Acc | Acc | Acc | Acc | Acc | Acc | Acc | Exact/F1| Acc| Acc
-ERNIE 1.0-Base-zh-CW | 12L768H | <b>76.44</b> | 76.04 |    58.02 |    60.87 |    83.56 | 78.61 |    89.14 |    84.00 |  72.26/90.40 |    84.73 |    77.15 |
+ERNIE 1.0-Base-zh-cw | 12L768H | <b>76.47</b> | 76.04 |    57.86 |    59.91 |   <b>83.41</b> | 79.58 |    89.91 |    83.42 |  72.88/90.78 |    <b>84.68</b> |    76.98 |
 ERNIE 2.0-Base-zh | 12L768H | 74.32  | 75.65 |  58.25 | 61.64 |  82.62 |  78.71 |    81.91 |  82.33 | 66.08/87.46    | 82.78    | 73.19
 ERNIE 1.0-Base-zh | 12L768H | 74.17 | 74.84 |    58.91 |    62.25 |    81.68 |    76.58 |    85.20 |    82.77 | 67.32/87.83 | 82.47 | 69.68
 
 
 <a name="ernie-1.0-large-zh-cw"> </a>
 
-### 4.2 ERNIE 1.0-Large-zh-CW 模型
+### 4.2 ERNIE 1.0-Large-zh-cw 模型
 
 除了base模型外，我们还训练了large模型。命名为`ernie-1.0-large-zh-cw`。使用开源语料，batch_size 512, 训练 400w step，训练去除SOP任务，只保留MLM损失，使用CLUE benchmark 对最优超参数进行GradSearch搜索：
 
 Model&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;  | Arch | CLUE AVG |  AFQMC | TNEWS | IFLYTEK | CMNLI | OCNLI | CLUE WSC2020 | CSL | CMRC | CHID | C3
 -- | -- | -- | -- | -- | -- | -- |  -- | -- | -- | -- | -- |  -- |
 Metrics |   |   | Acc | Acc | Acc | Acc | Acc | Acc | Acc | Exact/F1 | Acc| Acc
-ERNIE 1.0-Large-zh-CW| 24L1024H | <b>79.03</b> | 75.97 |    59.65 |    62.91 |    85.09 |    81.73| 93.09 |    84.53 | 74.22/91.88 | 88.57 | 84.54
+ERNIE 1.0-Large-zh-cw| 24L1024H | <b>79.03</b> | 75.97 |    59.65 |    62.91 |    85.09 |    81.73| 93.09 |    84.53 | 74.22/91.88 | 88.57 | 84.54
 ERNIE 3.0-Xbase-zh| 20L1024H | 78.39 | 76.16 | 59.55 | 61.87 | 84.40 |  81.73 | 88.82 | 83.60 |    75.99/93.00 | 86.78 | 84.98
 RoBERTa-wwm-ext-large | 24L1024H | 76.61 |    76.00 |    59.33 |    62.02 |    83.88 |    78.81 |    90.79 |    83.67 |    70.58/89.82 |    85.72 |    75.26
 

diff --git a/model_zoo/ernie-1.0/run_pretrain.py b/model_zoo/ernie-1.0/run_pretrain.py
@@ -541,8 +541,11 @@ def do_train(args):
             ctx_manager = contextlib.nullcontext() if sys.version_info >= (
                 3, 7) else contextlib.suppress()
 
-            if worker_num > 1 and (args.use_recompute
-                                   or args.accumulate_steps > 1):
+            if worker_num > 1 and (args.use_recompute or
+                                   ((step + 1) % args.accumulate_steps != 0)):
+                # grad acc, no_sync when (step + 1) % args.accumulate_steps != 0:
+                # recompute, no_sync every where
+                # recompute + grad_acc, no_sync every where
                 ctx_manager = model.no_sync()
             else:
                 ctx_manager = contextlib.nullcontext() if sys.version_info >= (

diff --git a/model_zoo/ernie-3.0/README.md b/model_zoo/ernie-3.0/README.md
@@ -139,7 +139,7 @@ batch_size=32 和 1，预测精度为 FP16 时，GPU 下的效果-时延图：
         <tr>
             <td rowspan=3 align=center> 24L1024H </td>
             <td style="text-align:center">
-                <span style="font-size:18px">ERNIE 1.0-Large-CW</span>
+                <span style="font-size:18px">ERNIE 1.0-Large-cw</span>
             </td>
             <td style="text-align:center">
                 <span style="font-size:18px"><b>79.03</b></span>
@@ -291,7 +291,7 @@ batch_size=32 和 1，预测精度为 FP16 时，GPU 下的效果-时延图：
             </td>
         </tr>
         <tr>
-            <td rowspan=8 align=center> 12L768H </td>
+            <td rowspan=9 align=center> 12L768H </td>
             <td style="text-align:center">
                 <span style="font-size:18px">
                     <a href="https://bj.bcebos.com/paddlenlp/models/transformers/ernie_3.0/ernie_3.0_base_zh.pdparams">
@@ -333,6 +333,44 @@ batch_size=32 和 1，预测精度为 FP16 时，GPU 下的效果-时延图：
                 <span style="font-size:18px"><b>77.88</b></span>
             </td>
         </tr>
+        <tr>
+            <td style="text-align:center">
+                <span style="font-size:18px">ERNIE 1.0-Base-zh-cw</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">76.47</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">76.07</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">57.86</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">59.91</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">83.41</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">79.58</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">89.91</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">83.42</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">72.88/90.78</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">84.68</span>
+            </td>
+            <td style="text-align:center">
+                <span style="font-size:18px">76.98</span>
+            </td>
+        </tr>
         <tr>
             <td style="text-align:center">
                 <span style="font-size:18px">ERNIE-Gram-zh</span>