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mengzi-bert-base

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@@ -22,10 +22,10 @@ model = BertModel.from_pretrained("Langboat/mengzi-bert-base")
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  ```
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  ## Scores on nine chinese tasks (without any data augmentation)
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- |Model|AFQMC|TNEWS|IFLYTEK|CMNLI|WSC|CSL|CMRC|C3|CHID|
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  |-|-|-|-|-|-|-|-|-|-|
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- |RoBERTa-wwm-ext|74.04|56.94|60.31|80.51|67.80|81.00|75.20|66.50|83.62|
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- |Mengzi-BERT-base|74.58|57.97|60.68|82.12|87.50|85.40|78.54|71.70|84.16|
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  RoBERTa-wwm-ext scores are from CLUE baseline
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  ```
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  ## Scores on nine chinese tasks (without any data augmentation)
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+ | Model | AFQMC | TNEWS | IFLYTEK | CMNLI | WSC | CSL | CMRC2018 | C3 | CHID |
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  |-|-|-|-|-|-|-|-|-|-|
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+ |RoBERTa-wwm-ext| 74.30 | 57.51 | 60.80 | 80.70 | 67.20 | 80.67 | 77.59 | 67.06 | 83.78 |
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+ |Mengzi-BERT-base| 74.58 | 57.97 | 60.68 | 82.12 | 87.50 | 85.40 | 78.54 | 71.70 | 84.16 |
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  RoBERTa-wwm-ext scores are from CLUE baseline
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