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asadfgglie
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mDeBERTa-v3-base-xnli-multilingual-zeroshot-v1.0

Zero-Shot Classification
PyTorch
Chinese
deberta-v2
Model card Files Community
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@@ -12,5 +12,16 @@ pipeline_tag: zero-shot-classification
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  |Datasets|asadfgglie/nli-zh-tw-all/test|asadfgglie/BanBan_2024-10-17-facial_expressions-nli/test|eval_dataset|test_dataset|
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  | :---: | :---: | :---: | :---: | :---: |
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- |Accuracy|0.874|0.559|0.839|0.843|
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- |Inference text/sec (RTX4060ti, batch=128)|37.0|233.0|37.0|37.0|
 
 
 
 
 
 
 
 
 
 
 
 
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  |Datasets|asadfgglie/nli-zh-tw-all/test|asadfgglie/BanBan_2024-10-17-facial_expressions-nli/test|eval_dataset|test_dataset|
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  | :---: | :---: | :---: | :---: | :---: |
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+ |eval_loss|0.362|1.554|0.496|0.478|
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+ |eval_f1_macro|0.872|0.516|0.835|0.841|
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+ |eval_f1_micro|0.874|0.559|0.839|0.843|
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+ |eval_accuracy_balanced|0.871|0.558|0.833|0.839|
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+ |eval_accuracy|0.874|0.559|0.839|0.843|
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+ |eval_precision_macro|0.874|0.59|0.839|0.847|
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+ |eval_recall_macro|0.871|0.558|0.833|0.839|
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+ |eval_precision_micro|0.874|0.559|0.839|0.843|
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+ |eval_recall_micro|0.874|0.559|0.839|0.843|
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+ |eval_runtime|230.697|4.066|51.216|203.905|
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+ |eval_samples_per_second|36.845|232.653|36.883|37.061|
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+ |eval_steps_per_second|0.29|1.967|0.293|0.294|
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+ |Size of dataset|8500|946|1889|7557|