MoritzLaurer
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xlm-v-base-mnli-xnli

Zero-Shot Classification

text-classification

Inference Endpoints

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MoritzLaurer HF staff commited on Feb 9, 2023

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@@ -122,12 +122,12 @@ This difference comes probably from mDeBERTa-v3's improved pre-training objectiv
 Depending on the task, it is probably better to use [mDeBERTa-v3-base-mnli-xnli](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli),
 but XLM-V could be better on some languages based on its improved vocabulary.
-|Datasets|ar|bg|de|el|en|es|fr|hi|ru|sw|th|tr|ur|vi|zh|average
 | :---:  | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |:---: |
-|Accuracy|0.757|0.808|0.796|0.79|0.856|0.814|0.806|0.751|0.782|0.725|0.757|0.766|0.729|0.784|0.782|0.780|
-|Speed (text/sec)|3501.0|3324.0|3438.0|3174.0|3713.0|3500.0|3129.0|3042.0|3419.0|3468.0|3782.0|3772.0|3099.0|3117.0|4217.0|na|
-|Datasets|mnli_m|mnli_mm|
 | :---: | :---: | :---: |
 |Accuracy|0.852|0.854|
 |Speed (text/sec)|2098.0|2170.0|

 Depending on the task, it is probably better to use [mDeBERTa-v3-base-mnli-xnli](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli),
 but XLM-V could be better on some languages based on its improved vocabulary.
+|Datasets|average|ar|bg|de|el|en|es|fr|hi|ru|sw|th|tr|ur|vi|zh|
 | :---:  | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |:---: |
+|Accuracy|0.780|0.757|0.808|0.796|0.79|0.856|0.814|0.806|0.751|0.782|0.725|0.757|0.766|0.729|0.784|0.782|
+|Speed (text/sec)|na|3501.0|3324.0|3438.0|3174.0|3713.0|3500.0|3129.0|3042.0|3419.0|3468.0|3782.0|3772.0|3099.0|3117.0|4217.0|
+|Datasets|mnli_m (en)|mnli_mm (en)|
 | :---: | :---: | :---: |
 |Accuracy|0.852|0.854|
 |Speed (text/sec)|2098.0|2170.0|