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MBERT_uncased_CrossEntropyLoss_adalora

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jslai//content/sample_data/best_models//MBERT_uncased_CrossEntropyLoss_adalora

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  1. README.md +11 -11
  2. adapter_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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- - Loss: 0.6758
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- - Accuracy: 0.711
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- - F1: 0.8311
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- - Precision: 0.7204
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- - Recall: 0.9820
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- - Roc Auc: 0.4910
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  ## Model description
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
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- | No log | 0.992 | 31 | 0.6902 | 0.621 | 0.7633 | 0.6967 | 0.8439 | 0.4401 |
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- | No log | 1.984 | 62 | 0.6792 | 0.702 | 0.8249 | 0.7178 | 0.9696 | 0.4848 |
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- | No log | 2.976 | 93 | 0.6758 | 0.711 | 0.8311 | 0.7204 | 0.9820 | 0.4910 |
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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: 0.67
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+ - F1: 0.8005
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+ - Precision: 0.7118
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+ - Recall: 0.9144
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+ - Roc Auc: 0.4717
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+ - Loss: 0.6634
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  ## Model description
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  ### Training results
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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 | 31 | 0.636 | 0.7745 | 0.7022 | 0.8633 | 0.4516 | 0.6726 |
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+ | No log | 1.984 | 62 | 0.662 | 0.7947 | 0.7093 | 0.9033 | 0.4662 | 0.6656 |
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+ | No log | 2.976 | 93 | 0.67 | 0.8005 | 0.7118 | 0.9144 | 0.4717 | 0.6634 |
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  ### Framework versions
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