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End of training

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README.md CHANGED
@@ -18,12 +18,12 @@ 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-cased](https://huggingface.co/google-bert/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: 0.5967
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- - Accuracy: 0.9591
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- - 1-f1: 0.45
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- - 1-recall: 0.4737
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- - 1-precision: 0.4286
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- - Balanced Acc: 0.7253
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  ## Model description
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@@ -55,12 +55,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
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- | 0.0535 | 1.0 | 17 | 0.4046 | 0.9721 | 0.4828 | 0.3684 | 0.7 | 0.6813 |
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- | 0.0941 | 2.0 | 34 | 0.2716 | 0.9591 | 0.5 | 0.5789 | 0.44 | 0.7760 |
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- | 0.0907 | 3.0 | 51 | 0.3408 | 0.9628 | 0.5238 | 0.5789 | 0.4783 | 0.7779 |
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- | 0.0071 | 4.0 | 68 | 0.2301 | 0.9591 | 0.5769 | 0.7895 | 0.4545 | 0.8774 |
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- | 0.0198 | 5.0 | 85 | 0.3545 | 0.9610 | 0.5333 | 0.6316 | 0.4615 | 0.8023 |
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- | 0.0226 | 6.0 | 102 | 0.5967 | 0.9591 | 0.45 | 0.4737 | 0.4286 | 0.7253 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/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: 0.6131
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+ - Accuracy: 0.9628
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+ - 1-f1: 0.4444
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+ - 1-recall: 0.4211
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+ - 1-precision: 0.4706
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+ - Balanced Acc: 0.7019
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
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+ | 0.1179 | 1.0 | 17 | 0.2541 | 0.9480 | 0.4167 | 0.5263 | 0.3448 | 0.7449 |
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+ | 0.1074 | 2.0 | 34 | 0.5716 | 0.9591 | 0.3529 | 0.3158 | 0.4 | 0.6492 |
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+ | 0.0526 | 3.0 | 51 | 0.6131 | 0.9628 | 0.4444 | 0.4211 | 0.4706 | 0.7019 |
 
 
 
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  ### Framework versions
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