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61347023S
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xtremedistil-l6-h384-uncased-v2.0

PyTorch
bert
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@@ -57,25 +57,21 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
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- | 0.6275 | 0.17 | 200 | 0.6177 | 0.3647 | 0.5463 | 0.5039 | 0.5463 | 0.6163 | 0.5039 | 0.5463 | 0.5463 |
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- | 0.5811 | 0.34 | 400 | 0.5808 | 0.5807 | 0.6194 | 0.5976 | 0.6194 | 0.6331 | 0.5976 | 0.6194 | 0.6194 |
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- | 0.5769 | 0.51 | 600 | 0.5680 | 0.6564 | 0.6585 | 0.6703 | 0.6585 | 0.6796 | 0.6703 | 0.6585 | 0.6585 |
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- | 0.5647 | 0.68 | 800 | 0.5634 | 0.6703 | 0.6728 | 0.6855 | 0.6728 | 0.6976 | 0.6855 | 0.6728 | 0.6728 |
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- | 0.5607 | 0.85 | 1000 | 0.5720 | 0.6176 | 0.6448 | 0.6264 | 0.6448 | 0.6569 | 0.6264 | 0.6448 | 0.6448 |
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- | 0.5645 | 1.02 | 1200 | 0.5617 | 0.6523 | 0.6601 | 0.6521 | 0.6601 | 0.6581 | 0.6521 | 0.6601 | 0.6601 |
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- | 0.5665 | 1.19 | 1400 | 0.5479 | 0.6802 | 0.6840 | 0.6986 | 0.6840 | 0.7172 | 0.6986 | 0.6840 | 0.6840 |
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- | 0.5432 | 1.35 | 1600 | 0.5540 | 0.6642 | 0.6665 | 0.6644 | 0.6665 | 0.6641 | 0.6644 | 0.6665 | 0.6665 |
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- | 0.5427 | 1.52 | 1800 | 0.5520 | 0.6533 | 0.6617 | 0.6532 | 0.6617 | 0.6601 | 0.6532 | 0.6617 | 0.6617 |
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- | 0.5453 | 1.69 | 2000 | 0.5487 | 0.6756 | 0.6781 | 0.6755 | 0.6781 | 0.6757 | 0.6755 | 0.6781 | 0.6781 |
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- | 0.5528 | 1.86 | 2200 | 0.5492 | 0.6720 | 0.6771 | 0.6713 | 0.6771 | 0.6747 | 0.6713 | 0.6771 | 0.6771 |
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- | 0.531 | 2.03 | 2400 | 0.5476 | 0.6799 | 0.6803 | 0.6882 | 0.6803 | 0.6911 | 0.6882 | 0.6803 | 0.6803 |
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- | 0.5199 | 2.2 | 2600 | 0.5454 | 0.6823 | 0.6824 | 0.6863 | 0.6824 | 0.6856 | 0.6863 | 0.6824 | 0.6824 |
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- | 0.535 | 2.37 | 2800 | 0.5441 | 0.6797 | 0.6803 | 0.6817 | 0.6803 | 0.6804 | 0.6817 | 0.6803 | 0.6803 |
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- | 0.5246 | 2.54 | 3000 | 0.5453 | 0.6746 | 0.6750 | 0.6771 | 0.6750 | 0.6759 | 0.6771 | 0.6750 | 0.6750 |
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- | 0.5405 | 2.71 | 3200 | 0.5408 | 0.6824 | 0.6861 | 0.6819 | 0.6861 | 0.6836 | 0.6819 | 0.6861 | 0.6861 |
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- | 0.5414 | 2.88 | 3400 | 0.5404 | 0.6826 | 0.6834 | 0.6841 | 0.6834 | 0.6828 | 0.6841 | 0.6834 | 0.6834 |
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  ### eval result
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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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  ### Training results
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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|0.511|0.701|0.539|0.528|
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+ |eval_f1_macro|0.717|0.488|0.684|0.7|
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+ |eval_f1_micro|0.718|0.506|0.684|0.7|
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+ |eval_accuracy_balanced|0.719|0.501|0.687|0.702|
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+ |eval_accuracy|0.718|0.506|0.684|0.7|
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+ |eval_precision_macro|0.718|0.501|0.686|0.701|
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+ |eval_recall_macro|0.719|0.501|0.687|0.702|
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+ |eval_precision_micro|0.718|0.506|0.684|0.7|
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+ |eval_recall_micro|0.718|0.506|0.684|0.7|
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+ |eval_runtime|8.805|0.188|1.873|7.442|
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+ |eval_samples_per_second|965.397|5039.361|1008.401|1015.398|
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+ |eval_steps_per_second|7.61|42.616|8.007|8.062|
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+ |Size of dataset|8500|946|1889|7557|
 
 
 
 
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  ### eval result
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  |Datasets|asadfgglie/nli-zh-tw-all/test|asadfgglie/BanBan_2024-10-17-facial_expressions-nli/test|eval_dataset|test_dataset|