IDEA-CCNL
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Erlangshen-DeBERTa-v2-97M-Chinese

Inference Endpoints

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gxy commited on Oct 20, 2022

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@@ -45,10 +45,13 @@ To get a Chinese DeBERTa-v2-Base (97M), we use WuDao Corpora (180 GB version) fo
 We present the results (dev set) on the following tasks:
-| Model                              | OCNLI | CMNLI  |
-| ---------------------------------- | ----- | ------ |
-| RoBERTa-base                       | 0.743 | 0.7973 |
-| Erlangshen-Deberta-97M-Chinese     | 0.752 | 0.807  |
 ## 使用 Usage

 We present the results (dev set) on the following tasks:
+| Model                                                                                                                            | AFQMC  | TNEWS1.1 | IFLYTEK | OCNLI  | CMNLI  |
+| -------------------------------------------------------------------------------------------------------------------------------- | ------ | -------- | ------- | ------ | ------ |
+| RoBERTa-base                                                                                                                     | 0.7406 | 0.575    | 0.6036  | 0.743  | 0.7973 |
+| RoBERTa-large                                                                                                                    | 0.7488 | 0.5879   | 0.6152  | 0.777  | 0.814  |
+| **[IDEA-CCNL/Erlangshen-DeBERTa-v2-97M-Chinese](https://huggingface.co/IDEA-CCNL/Erlangshen-DeBERTa-v2-97M-Chinese)**            | 0.7405 | 0.571    | 0.5977  | 0.7568 | 0.807  |
+| [IDEA-CCNL/Erlangshen-DeBERTa-v2-320M-Chinese](https://huggingface.co/IDEA-CCNL/Erlangshen-DeBERTa-v2-320M-Chinese)              | 0.7498 | 0.5817   | 0.6042  | 0.8022 | 0.8301 |
+| [IDEA-CCNL/Erlangshen-DeBERTa-v2-710M-Chinese](https://huggingface.co/IDEA-CCNL/Erlangshen-DeBERTa-v2-710M-Chinese)              | 0.7549 | 0.5873   | 0.6177  | 0.8012 | 0.8389 |
 ## 使用 Usage