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roberta-base-ca-v2

Fill-Mask
Transformers
PyTorch
Catalan
roberta
catalan
masked-lm
RoBERTa-base-ca-v2
CaText
Catalan Textual Corpus
Inference Endpoints
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@@ -89,7 +89,7 @@ Here are the train/dev/test splits of the datasets:
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  | Task | NER (F1) | POS (F1) | STS (Pearson) | TC (accuracy) | QA (ViquiQuAD) (F1/EM) | QA (XQuAD) (F1/EM) |
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  | ------------|:-------------:| -----:|:------|:-------|:------|:----|
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- | RoBERTa-base-ca-v2 | **89.80** | **99.10** | **80.00** | **83.40** | **88.00/72.29** | **71.50** |
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  | BERTa | 88.13 | 98.97 | 79.73 | 74.16 | 86.97/72.29 | 68.89/48.87 |
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  | mBERT | 86.38 | 98.82 | 76.34 | 70.56 | 86.97/72.22 | 67.15/46.51 |
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  | XLM-RoBERTa | 87.66 | 98.89 | 75.40 | 71.68 | 85.50/70.47 | 67.10/46.42 |
 
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  | Task | NER (F1) | POS (F1) | STS (Pearson) | TC (accuracy) | QA (ViquiQuAD) (F1/EM) | QA (XQuAD) (F1/EM) |
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  | ------------|:-------------:| -----:|:------|:-------|:------|:----|
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+ | RoBERTa-base-ca-v2 | **89.80** | **99.10** | **80.00** | **83.40** | **88.00** | **71.50** |
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  | BERTa | 88.13 | 98.97 | 79.73 | 74.16 | 86.97/72.29 | 68.89/48.87 |
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  | mBERT | 86.38 | 98.82 | 76.34 | 70.56 | 86.97/72.22 | 67.15/46.51 |
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  | XLM-RoBERTa | 87.66 | 98.89 | 75.40 | 71.68 | 85.50/70.47 | 67.10/46.42 |