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mjwong
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e5-large-mnli

Zero-Shot Classification
Transformers
PyTorch
Safetensors
English
bert
text-classification
Inference Endpoints
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@@ -56,7 +56,7 @@ classifier(sequence_to_classify, candidate_labels, multi_class=True)
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  ### Eval results
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  The model was evaluated using the dev sets for MultiNLI and test sets for ANLI. The metric used is accuracy.
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- |Datasets|mnli_dev_m|mnli_dev_mm|anli_test_r1|anli_test_r2|anli_test_r2|
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  | :---: | :---: | :---: | :---: | :---: | :---: |
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  |[e5-base-mnli](https://huggingface.co/mjwong/e5-base-mnli)|0.840|0.839|0.231|0.285|0.309|
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  |[e5-large-mnli](https://huggingface.co/mjwong/e5-large-mnli)|0.868|0.869|0.301|0.296|0.294|
 
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  ### Eval results
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  The model was evaluated using the dev sets for MultiNLI and test sets for ANLI. The metric used is accuracy.
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+ |Datasets|mnli_dev_m|mnli_dev_mm|anli_test_r1|anli_test_r2|anli_test_r3|
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  | :---: | :---: | :---: | :---: | :---: | :---: |
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  |[e5-base-mnli](https://huggingface.co/mjwong/e5-base-mnli)|0.840|0.839|0.231|0.285|0.309|
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  |[e5-large-mnli](https://huggingface.co/mjwong/e5-large-mnli)|0.868|0.869|0.301|0.296|0.294|