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airaria · Apr 26, 2020 · c3eccad · c3eccad
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diff --git a/README_ZH.md b/README_ZH.md
@@ -198,7 +198,7 @@ with distiller:
 **更多的示例可参见`examples`文件夹：**
 
 * [examples/random_token_example](examples/random_token_example): 一个可运行的简单示例，在文本分类任务上以随机文本为输入，演示TextBrewer用法。
-* [examples/cmrc2018\_example](examples/cmrc2018_example) (中文): CMRC2018上的中文阅读理解任务蒸馏，并使用DRCD数据集做数据增强。
+* [examples/cmrc2018\_example](examples/cmrc2018_example) (中文): CMRC 2018上的中文阅读理解任务蒸馏，并使用DRCD数据集做数据增强。
 * [examples/mnli\_example](examples/mnli_example) (英文): MNLI任务上的英文句对分类任务蒸馏，并展示如何使用多教师蒸馏。
 * [examples/conll2003_example](examples/conll2003_example) (英文): CoNLL-2003英文实体识别任务上的序列标注任务蒸馏。
 
@@ -333,8 +333,8 @@ Our results:
 
 说明：
 
-1. 以RoBERTa-wwm-ext为教师模型蒸馏CMRC2018和DRCD时，不采用学习率衰减
-2. CMRC2018和DRCD两个任务上蒸馏时他们互作为增强数据
+1. 以RoBERTa-wwm-ext为教师模型蒸馏CMRC 2018和DRCD时，不采用学习率衰减
+2. CMRC 2018和DRCD两个任务上蒸馏时他们互作为增强数据
 3. Electra-base的教师模型训练设置参考自[**Chinese-ELECTRA**](https://github.com/ymcui/Chinese-ELECTRA)
 4. Electra-small学生模型采用[预训练权重](https://github.com/ymcui/Chinese-ELECTRA)初始化
 

diff --git a/docs/source/Experiments.md b/docs/source/Experiments.md
@@ -139,7 +139,7 @@ The results are listed below (see [Experimental Results](ExperimentResults.md) f
 
 **Note**:
 
-1. Learning rate decay is not used in distillation on CMRC2018 and DRCD.
-2. CMRC2018 and DRCD take each other as the augmentation dataset in the distillation.
+1. Learning rate decay is not used in distillation on CMRC 2018 and DRCD.
+2. CMRC 2018 and DRCD take each other as the augmentation dataset in the distillation.
 3. The settings of training Electra-base teacher model can be found at [**Chinese-ELECTRA**](https://github.com/ymcui/Chinese-ELECTRA).
 4. Electra-small student model is intialized with the [pretrained weights](https://github.com/ymcui/Chinese-ELECTRA).
diff --git a/docs/source/Tutorial.rst b/docs/source/Tutorial.rst
@@ -130,7 +130,7 @@ Examples
 Examples can be found in the `examples <https://github.com/airaria/TextBrewer/tree/master/examples>`_ directory of the repo:
 
 * `examples/random_token_example <https://github.com/airaria/TextBrewer/tree/master/examples/random_tokens_example>`_ : a simple runnable toy example which demonstrates the usage of TextBrewer. This example performs distillation on the text classification task with random tokens as inputs.
-* `examples/cmrc2018\_example <https://github.com/airaria/TextBrewer/tree/master/examples/cmrc2018_example>`_ (Chinese): distillation on CMRC2018, a Chinese MRC task, using DRCD as data augmentation.
+* `examples/cmrc2018\_example <https://github.com/airaria/TextBrewer/tree/master/examples/cmrc2018_example>`_ (Chinese): distillation on CMRC 2018, a Chinese MRC task, using DRCD as data augmentation.
 * `examples/mnli\_example <https://github.com/airaria/TextBrewer/tree/master/examples/mnli_example>`_ (English): distillation on MNLI, an English sentence-pair classification task. This example also shows how to perform multi-teacher distillation.
 * `examples/conll2003_example <https://github.com/airaria/TextBrewer/tree/master/examples/conll2003_example>`_ (English): distillation on CoNLL-2003 English NER task, which is in the form of sequence labeling.