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End of training

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README.md CHANGED
@@ -20,10 +20,10 @@ 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: 0.1977
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- - Accuracy: 0.9383
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- - F1: 0.2445
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- - Recall: 0.1628
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  ## Model description
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@@ -43,8 +43,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
@@ -55,9 +55,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
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- | 0.2118 | 1.0 | 701 | 0.2022 | 0.9340 | 0.1148 | 0.0698 |
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- | 0.1864 | 2.0 | 1402 | 0.2178 | 0.9397 | 0.0452 | 0.0233 |
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- | 0.1275 | 3.0 | 2103 | 0.1977 | 0.9383 | 0.2445 | 0.1628 |
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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: 0.1984
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+ - Accuracy: 0.9369
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+ - F1: 0.3059
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+ - Recall: 0.2267
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
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+ | No log | 1.0 | 351 | 0.1665 | 0.9401 | 0.16 | 0.0930 |
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+ | 0.1813 | 2.0 | 702 | 0.2099 | 0.9418 | 0.1189 | 0.0640 |
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+ | 0.1067 | 3.0 | 1053 | 0.1984 | 0.9369 | 0.3059 | 0.2267 |
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  ### Framework versions
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