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MBERT_uncased_CrossEntropyLoss_lora

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jslai//content/sample_data/best_models//MBERT_uncased_CrossEntropyLoss_lora

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  1. README.md +6 -6
  2. adapter/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: 0.6924
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  - Accuracy: 0.518
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  - F1: 0.6730
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  - Precision: 0.6613
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  - Recall: 0.6851
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  - Roc Auc: 0.3824
 
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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 | 0.7081 | 0.347 | 0.4287 | 0.5847 | 0.3384 | 0.3540 |
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- | No log | 1.984 | 62 | 0.6961 | 0.479 | 0.6354 | 0.6440 | 0.6271 | 0.3588 |
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- | No log | 2.976 | 93 | 0.6924 | 0.518 | 0.6730 | 0.6613 | 0.6851 | 0.3824 |
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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: 0.518
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  - F1: 0.6730
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  - Precision: 0.6613
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  - Recall: 0.6851
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  - Roc Auc: 0.3824
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+ - Loss: 0.6924
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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 | 0.347 | 0.4287 | 0.5847 | 0.3384 | 0.3540 | 0.7081 |
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+ | No log | 1.984 | 62 | 0.479 | 0.6354 | 0.6440 | 0.6271 | 0.3588 | 0.6961 |
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+ | No log | 2.976 | 93 | 0.518 | 0.6730 | 0.6613 | 0.6851 | 0.3824 | 0.6924 |
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  ### Framework versions
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