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End of training

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README.md CHANGED
@@ -20,11 +20,11 @@ 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: 0.1337
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- - Precision: 0.7867
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- - Recall: 0.8827
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- - F1: 0.8320
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- - Accuracy: 0.9727
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  ## Model description
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@@ -55,21 +55,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 276 | 0.1785 | 0.6910 | 0.6597 | 0.6750 | 0.9527 |
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- | 0.2507 | 2.0 | 552 | 0.1321 | 0.7761 | 0.7689 | 0.7725 | 0.9630 |
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- | 0.2507 | 3.0 | 828 | 0.1158 | 0.7691 | 0.8165 | 0.7921 | 0.9669 |
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- | 0.084 | 4.0 | 1104 | 0.1186 | 0.7503 | 0.8479 | 0.7961 | 0.9668 |
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- | 0.084 | 5.0 | 1380 | 0.1287 | 0.7629 | 0.8560 | 0.8068 | 0.9657 |
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- | 0.0443 | 6.0 | 1656 | 0.1295 | 0.7453 | 0.8769 | 0.8058 | 0.9666 |
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- | 0.0443 | 7.0 | 1932 | 0.1423 | 0.7592 | 0.8862 | 0.8178 | 0.9685 |
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- | 0.0243 | 8.0 | 2208 | 0.1267 | 0.7970 | 0.8664 | 0.8303 | 0.9724 |
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- | 0.0243 | 9.0 | 2484 | 0.1309 | 0.7747 | 0.8746 | 0.8216 | 0.9710 |
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- | 0.0164 | 10.0 | 2760 | 0.1337 | 0.7867 | 0.8827 | 0.8320 | 0.9727 |
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  ### Framework versions
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- - Transformers 4.41.1
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  - Pytorch 2.3.0+cu121
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- - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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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: 0.1210
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+ - Precision: 0.8205
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+ - Recall: 0.8757
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+ - F1: 0.8472
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+ - Accuracy: 0.9760
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 276 | 0.1670 | 0.7138 | 0.6690 | 0.6906 | 0.9555 |
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+ | 0.247 | 2.0 | 552 | 0.1192 | 0.8109 | 0.7770 | 0.7936 | 0.9676 |
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+ | 0.247 | 3.0 | 828 | 0.1181 | 0.8226 | 0.8188 | 0.8207 | 0.9709 |
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+ | 0.0846 | 4.0 | 1104 | 0.1162 | 0.7656 | 0.8571 | 0.8088 | 0.9685 |
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+ | 0.0846 | 5.0 | 1380 | 0.1248 | 0.7627 | 0.8699 | 0.8128 | 0.9687 |
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+ | 0.0442 | 6.0 | 1656 | 0.0982 | 0.8233 | 0.8931 | 0.8568 | 0.9777 |
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+ | 0.0442 | 7.0 | 1932 | 0.1114 | 0.8100 | 0.8862 | 0.8464 | 0.9741 |
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+ | 0.0247 | 8.0 | 2208 | 0.1164 | 0.8342 | 0.8885 | 0.8605 | 0.9780 |
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+ | 0.0247 | 9.0 | 2484 | 0.1208 | 0.7983 | 0.8920 | 0.8426 | 0.9746 |
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+ | 0.0159 | 10.0 | 2760 | 0.1210 | 0.8205 | 0.8757 | 0.8472 | 0.9760 |
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  ### Framework versions
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+ - Transformers 4.41.2
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  - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.2
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  - Tokenizers 0.19.1
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