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roberta-base-ca-v2

RoBERTa-base-ca-v2

Catalan Textual Corpus

Inference Endpoints

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asier-gutierrez commited on Jun 1, 2022

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@@ -99,7 +99,7 @@ Here are the train/dev/test splits of the datasets:
 | Task        | NER (F1)      | POS (F1)   | STS (Pearson)   | TC (accuracy) | QA (ViquiQuAD) (F1/EM)  | QA (XQuAD) (F1/EM) |
 | ------------|:-------------:| -----:|:------|:-------|:------|:----|
-| RoBERTa-base-ca-v2       | **89.80** | **99.10** | **80.00** | **83.40** | **88.00** | **71.50** |
 | BERTa       | 88.13 | 98.97 | 79.73 | 74.16 | 86.97/72.29 | 68.89/48.87 |
 | mBERT       | 86.38 | 98.82 | 76.34 | 70.56 | 86.97/72.22 | 67.15/46.51 |
 | XLM-RoBERTa | 87.66 | 98.89 | 75.40 | 71.68 | 85.50/70.47 | 67.10/46.42 |

 | Task        | NER (F1)      | POS (F1)   | STS (Pearson)   | TC (accuracy) | QA (ViquiQuAD) (F1/EM)  | QA (XQuAD) (F1/EM) |
 | ------------|:-------------:| -----:|:------|:-------|:------|:----|
+| RoBERTa-base-ca-v2       | **89.84** | **99.07** | **79.98** | **83.41** | **88.04/74.65** | **71.50/53.41** |
 | BERTa       | 88.13 | 98.97 | 79.73 | 74.16 | 86.97/72.29 | 68.89/48.87 |
 | mBERT       | 86.38 | 98.82 | 76.34 | 70.56 | 86.97/72.22 | 67.15/46.51 |
 | XLM-RoBERTa | 87.66 | 98.89 | 75.40 | 71.68 | 85.50/70.47 | 67.10/46.42 |