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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 +9 -9
  2. adapter/adapter_model.safetensors +1 -1
  3. adapter_model.safetensors +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: 0.6759
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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 Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:|
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- | No log | 0.992 | 31 | 0.6903 | 0.622 | 0.7638 | 0.6975 | 0.8439 | 0.4419 |
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- | No log | 1.984 | 62 | 0.6794 | 0.702 | 0.8249 | 0.7178 | 0.9696 | 0.4848 |
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- | No log | 2.976 | 93 | 0.6759 | 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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+ - Loss: 0.6661
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+ - Accuracy: 0.724
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+ - F1: 0.8399
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+ - Precision: 0.724
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+ - Recall: 1.0
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+ - Roc Auc: 0.5
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  ## Model description
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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 | 0.6806 | 0.673 | 0.7940 | 0.7300 | 0.8702 | 0.5130 |
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+ | No log | 1.984 | 62 | 0.6696 | 0.724 | 0.8399 | 0.724 | 1.0 | 0.5 |
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+ | No log | 2.976 | 93 | 0.6661 | 0.724 | 0.8399 | 0.724 | 1.0 | 0.5 |
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  ### Framework versions
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