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End of training

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README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-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: 0.1534
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- - Accuracy: 0.9817
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  ## Model description
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@@ -49,18 +49,18 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.1014 | 0.8 | 300 | 0.2450 | 0.9433 |
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- | 0.0026 | 1.6 | 600 | 0.2036 | 0.9633 |
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- | 0.0007 | 2.4 | 900 | 0.1873 | 0.96 |
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- | 0.0019 | 3.2 | 1200 | 0.1421 | 0.98 |
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- | 0.0002 | 4.0 | 1500 | 0.1693 | 0.9717 |
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- | 0.0003 | 4.8 | 1800 | 0.2226 | 0.9683 |
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- | 0.0001 | 5.6 | 2100 | 0.1757 | 0.9767 |
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- | 0.0001 | 6.4 | 2400 | 0.2107 | 0.975 |
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- | 0.0003 | 7.2 | 2700 | 0.1350 | 0.9833 |
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- | 0.0001 | 8.0 | 3000 | 0.1507 | 0.9817 |
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- | 0.0001 | 8.8 | 3300 | 0.1525 | 0.9817 |
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- | 0.0001 | 9.6 | 3600 | 0.1534 | 0.9817 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-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: 0.1373
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+ - Accuracy: 0.98
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.098 | 0.8 | 300 | 0.2940 | 0.9283 |
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+ | 0.0022 | 1.6 | 600 | 0.2300 | 0.9517 |
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+ | 0.0008 | 2.4 | 900 | 0.1443 | 0.9733 |
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+ | 0.0004 | 3.2 | 1200 | 0.1842 | 0.9683 |
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+ | 0.0002 | 4.0 | 1500 | 0.1210 | 0.9817 |
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+ | 0.0001 | 4.8 | 1800 | 0.3007 | 0.96 |
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+ | 0.0001 | 5.6 | 2100 | 0.2417 | 0.9667 |
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+ | 0.009 | 6.4 | 2400 | 0.1693 | 0.975 |
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+ | 0.0001 | 7.2 | 2700 | 0.1276 | 0.985 |
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+ | 0.0001 | 8.0 | 3000 | 0.1330 | 0.98 |
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+ | 0.0001 | 8.8 | 3300 | 0.1363 | 0.98 |
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+ | 0.0001 | 9.6 | 3600 | 0.1373 | 0.98 |
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  ### Framework versions
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