Update README.md

README.md

@@ -30,12 +30,12 @@ Here are scores on the devlopment set of six Chinese tasks:
 
 | Model              | Score | book_review | chnsenticorp | lcqmc | tnews(CLUE) | iflytek(CLUE) | ocnli(CLUE) |
 | ------------------ | :---: | :----: | :----------: | :---: | :---------: | :-----------: | :---------: |
-| RoBERTa-Tiny-WWM   | 72.2  |  83.6  |     91.8     | 81.8  |    62.1     |     55.4      |    58.6     |
-| RoBERTa-Mini-WWM   | 76.3  |  86.2  |     93.0     | 86.8  |    64.4     |     58.7      |    68.8     |
+| RoBERTa-Tiny-WWM   | 72.2  |  83.7  |     91.8     | 81.8  |    62.1     |     55.4      |    58.6     |
+| RoBERTa-Mini-WWM   | 76.3  |  86.4  |     93.0     | 86.8  |    64.4     |     58.7      |    68.8     |
 | RoBERTa-Small-WWM  | 77.6  |  88.1  |     93.8     | 87.2  |    65.2     |     59.6      |    71.4     |
-| RoBERTa-Medium-WWM | 78.6  |  89.5  |     94.4     | 88.8  |    66.0     |     59.9      |    73.2     |
-| RoBERTa-Base-WWM   | 80.2  |  90.3  |     95.8     | 89.4  |    67.5     |     61.8      |    76.2     |
-| RoBERTa-Large-WWM  | 81.1  |  91.3  |     95.8     | 90.0  |    68.5     |     62.1      |    79.1     |
+| RoBERTa-Medium-WWM | 78.6  |  89.3  |     94.4     | 88.8  |    66.0     |     59.9      |    73.2     |
+| RoBERTa-Base-WWM   | 80.2  |  90.6  |     95.8     | 89.4  |    67.5     |     61.8      |    76.2     |
+| RoBERTa-Large-WWM  | 81.1  |  91.1  |     95.8     | 90.0  |    68.5     |     62.1      |    79.1     |
 
 For each task, we selected the best fine-tuning hyperparameters from the lists below, and trained with the sequence length of 128:
 
@@ -182,7 +182,6 @@ python3 scripts/convert_bert_from_uer_to_huggingface.py --input_model_path model
   journal={ACL 2023},
   pages={217},
   year={2023}
-
 ```
 
 [2_128]:https://huggingface.co/uer/roberta-tiny-wwm-chinese-cluecorpussmall