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README.md
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@@ -74,12 +75,12 @@ classifier(sequence_to_classify, candidate_labels, multi_label=True)
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```
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### Eval results
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The model was evaluated using the XNLI test sets on
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|Datasets|en|ar|bg|de|el|es|fr|ru|sw|th|tr|ur|vi|zh|
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| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
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|[multilingual-e5-base-xnli](https://huggingface.co/mjwong/multilingual-e5-base-xnli)|0.849|0.
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|[multilingual-e5-large-xnli](https://huggingface.co/mjwong/multilingual-e5-large-xnli)|0.867|0.
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### Training hyperparameters
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- el
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- hi
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```
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### Eval results
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The model was evaluated using the XNLI test sets on 15 languages: English (en), Arabic (ar), Bulgarian (bg), German (de), Greek (el), Spanish (es), French (fr), Hindi (hi), Russian (ru), Swahili (sw), Thai (th), Turkish (tr), Urdu (ur), Vietnam (vi) and Chinese (zh). The metric used is accuracy.
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|Datasets|en|ar|bg|de|el|es|fr|hi|ru|sw|th|tr|ur|vi|zh|
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| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
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|[multilingual-e5-base-xnli](https://huggingface.co/mjwong/multilingual-e5-base-xnli)|0.849|0.768|0.803|0.800|0.792|0.809|0.805|0.738|0.782|0.728|0.756|0.766|0.713|0.787|0.785|
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|[multilingual-e5-large-xnli](https://huggingface.co/mjwong/multilingual-e5-large-xnli)|0.867|0.791|0.832|0.825|0.823|0.837|0.824|0.778|0.806|0.749|0.787|0.793|0.738|0.813|0.808|
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### Training hyperparameters
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