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MBERT_uncased_GeneralizedCrossEntropy_full_ft

Text Classification
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bert
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jslai/MBERT_uncased_GeneralizedCrossEntropy_full_ft_word_order_head_to_tail_20241212-040432

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  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -21,12 +21,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Accuracy: 0.844
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- - F1: 0.8957
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- - Precision: 0.8656
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- - Recall: 0.9280
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- - Roc Auc: 0.7769
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- - Loss: 0.2209
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  ## Model description
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  | Training Loss | Epoch | Step | Accuracy | F1 | Precision | Recall | Roc Auc | Validation Loss |
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  |:-------------:|:-----:|:----:|:--------:|:------:|:---------:|:------:|:-------:|:---------------:|
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- | No log | 0.992 | 62 | 0.827 | 0.8816 | 0.8714 | 0.8920 | 0.7751 | 0.2555 |
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- | 0.3087 | 2.0 | 125 | 0.839 | 0.8936 | 0.8546 | 0.9363 | 0.7613 | 0.2308 |
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- | 0.3087 | 2.976 | 186 | 0.844 | 0.8957 | 0.8656 | 0.9280 | 0.7769 | 0.2209 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Accuracy: 0.802
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+ - F1: 0.8584
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+ - Precision: 0.8310
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+ - Recall: 0.8876
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+ - Roc Auc: 0.7555
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+ - Loss: 0.2729
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  ## Model description
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  | Training Loss | Epoch | Step | Accuracy | F1 | Precision | Recall | Roc Auc | Validation Loss |
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  |:-------------:|:-----:|:----:|:--------:|:------:|:---------:|:------:|:-------:|:---------------:|
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+ | No log | 0.992 | 62 | 0.77 | 0.8487 | 0.7642 | 0.9541 | 0.6700 | 0.3336 |
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+ | 0.3578 | 2.0 | 125 | 0.805 | 0.8567 | 0.8511 | 0.8624 | 0.7738 | 0.2695 |
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+ | 0.3578 | 2.976 | 186 | 0.802 | 0.8584 | 0.8310 | 0.8876 | 0.7555 | 0.2729 |
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  ### Framework versions
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