mjwong
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multilingual-e5-large-xnli-anli

Zero-Shot Classification

text-classification

Inference Endpoints

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mjwong commited on Jul 7

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@@ -104,7 +104,6 @@ The model was evaluated using the XNLI test sets on 15 languages: English (en),
 |[multilingual-e5-large-instruct-xnli](https://huggingface.co/mjwong/multilingual-e5-large-instruct-xnli)|0.864|0.793|0.839|0.821|0.824|0.837|0.823|0.770|0.810|0.744|0.784|0.791|0.716|0.807|0.807|
 |[multilingual-e5-large-instruct-xnli-anli](https://huggingface.co/mjwong/multilingual-e5-large-instruct-xnli-anli)|0.861|0.780|0.816|0.808|0.806|0.825|0.816|0.758|0.799|0.727|0.775|0.780|0.721|0.787|0.795|
 The model was also evaluated using the dev sets for MultiNLI and test sets for ANLI. The metric used is accuracy.
 |Datasets|mnli_dev_m|mnli_dev_mm|anli_test_r1|anli_test_r2|anli_test_r3|

 |[multilingual-e5-large-instruct-xnli](https://huggingface.co/mjwong/multilingual-e5-large-instruct-xnli)|0.864|0.793|0.839|0.821|0.824|0.837|0.823|0.770|0.810|0.744|0.784|0.791|0.716|0.807|0.807|
 |[multilingual-e5-large-instruct-xnli-anli](https://huggingface.co/mjwong/multilingual-e5-large-instruct-xnli-anli)|0.861|0.780|0.816|0.808|0.806|0.825|0.816|0.758|0.799|0.727|0.775|0.780|0.721|0.787|0.795|
 The model was also evaluated using the dev sets for MultiNLI and test sets for ANLI. The metric used is accuracy.
 |Datasets|mnli_dev_m|mnli_dev_mm|anli_test_r1|anli_test_r2|anli_test_r3|