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mt5-small-task3-dataset4

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README.md CHANGED
@@ -17,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5832
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- - Accuracy: 0.056
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- - Mse: 6.6919
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- - Log-distance: 0.6837
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- - S Score: 0.4844
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse | Log-distance | S Score |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:|
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- | 10.6622 | 1.0 | 250 | 2.1479 | 0.032 | 7.8307 | 0.8081 | 0.4244 |
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- | 3.1421 | 2.0 | 500 | 1.8253 | 0.044 | 5.7385 | 0.6844 | 0.4892 |
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- | 2.3451 | 3.0 | 750 | 1.6174 | 0.04 | 5.5959 | 0.6980 | 0.4832 |
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- | 2.0073 | 4.0 | 1000 | 1.5994 | 0.046 | 6.2422 | 0.6708 | 0.4940 |
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- | 1.8357 | 5.0 | 1250 | 1.5867 | 0.05 | 6.2493 | 0.6727 | 0.4936 |
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- | 1.7782 | 6.0 | 1500 | 1.5800 | 0.048 | 6.0314 | 0.6621 | 0.4980 |
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- | 1.7333 | 7.0 | 1750 | 1.5733 | 0.056 | 6.8849 | 0.6908 | 0.4816 |
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- | 1.7219 | 8.0 | 2000 | 1.6012 | 0.056 | 6.7969 | 0.6872 | 0.4828 |
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- | 1.6886 | 9.0 | 2250 | 1.5849 | 0.038 | 6.1512 | 0.6683 | 0.4976 |
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- | 1.6804 | 10.0 | 2500 | 1.5832 | 0.056 | 6.6919 | 0.6837 | 0.4844 |
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.15.0
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  - Tokenizers 0.15.0
 
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  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6024
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+ - Accuracy: 0.038
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+ - Mse: 6.4524
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+ - Log-distance: 0.6628
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+ - S Score: 0.4912
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse | Log-distance | S Score |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:|
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+ | 12.4369 | 1.0 | 250 | 2.2550 | 0.038 | 6.7116 | 0.6817 | 0.4748 |
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+ | 3.1387 | 2.0 | 500 | 1.8576 | 0.024 | 5.8813 | 0.7455 | 0.4552 |
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+ | 2.3265 | 3.0 | 750 | 1.6663 | 0.05 | 7.7168 | 0.7232 | 0.4556 |
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+ | 1.9955 | 4.0 | 1000 | 1.6121 | 0.04 | 6.3175 | 0.6614 | 0.4908 |
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+ | 1.8234 | 5.0 | 1250 | 1.6380 | 0.034 | 6.8099 | 0.6780 | 0.4860 |
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+ | 1.7591 | 6.0 | 1500 | 1.5953 | 0.04 | 6.3175 | 0.6614 | 0.4908 |
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+ | 1.7194 | 7.0 | 1750 | 1.5996 | 0.054 | 6.0821 | 0.6559 | 0.4976 |
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+ | 1.6988 | 8.0 | 2000 | 1.5970 | 0.048 | 6.6575 | 0.6618 | 0.4952 |
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+ | 1.6831 | 9.0 | 2250 | 1.6024 | 0.038 | 6.4524 | 0.6628 | 0.4912 |
 
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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  - Tokenizers 0.15.0
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