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bert-base-fine-tuned-text-classificarion-ds

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
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xet
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End of training

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  1. README.md +6 -6
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -20,7 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7094
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  - F1: 0.8593
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  - Recall: 0.9046
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  - Accuracy: 0.9046
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:---------:|
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- | 0.2549 | 1.0 | 1195 | 0.6842 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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- | 0.2395 | 2.0 | 2390 | 0.6760 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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- | 0.2638 | 3.0 | 3585 | 0.6620 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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- | 0.2576 | 4.0 | 4780 | 0.6567 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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- | 0.2516 | 5.0 | 5975 | 0.7094 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7043
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  - F1: 0.8593
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  - Recall: 0.9046
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  - Accuracy: 0.9046
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:---------:|
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+ | 0.2575 | 1.0 | 1195 | 0.6712 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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+ | 0.2478 | 2.0 | 2390 | 0.6663 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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+ | 0.254 | 3.0 | 3585 | 0.6704 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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+ | 0.2905 | 4.0 | 4780 | 0.6748 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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+ | 0.2531 | 5.0 | 5975 | 0.7043 | 0.8593 | 0.9046 | 0.9046 | 0.8183 |
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  ### Framework versions
pytorch_model.bin CHANGED
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