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End of training

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@@ -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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0797
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- - Precision: 0.5276
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- - Recall: 0.6297
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- - F1: 0.5742
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- - Accuracy: 0.9700
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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 | 55 | 0.1312 | 0.3091 | 0.3759 | 0.3392 | 0.9464 |
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- | No log | 2.0 | 110 | 0.0918 | 0.4431 | 0.4965 | 0.4683 | 0.9663 |
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- | No log | 3.0 | 165 | 0.0826 | 0.4836 | 0.6199 | 0.5433 | 0.9684 |
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- | No log | 4.0 | 220 | 0.0777 | 0.5189 | 0.6157 | 0.5632 | 0.9703 |
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- | No log | 5.0 | 275 | 0.0797 | 0.5276 | 0.6297 | 0.5742 | 0.9700 |
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  ### Framework versions
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- - Transformers 4.33.0
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  - Pytorch 2.0.1+cu118
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- - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0834
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+ - Precision: 0.5329
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+ - Recall: 0.6129
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+ - F1: 0.5701
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+ - Accuracy: 0.9689
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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 | 55 | 0.1363 | 0.2460 | 0.2987 | 0.2698 | 0.9436 |
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+ | No log | 2.0 | 110 | 0.0926 | 0.3943 | 0.4656 | 0.4270 | 0.9636 |
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+ | No log | 3.0 | 165 | 0.0823 | 0.4937 | 0.6059 | 0.5441 | 0.9683 |
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+ | No log | 4.0 | 220 | 0.0802 | 0.5187 | 0.5849 | 0.5498 | 0.9696 |
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+ | No log | 5.0 | 275 | 0.0834 | 0.5329 | 0.6129 | 0.5701 | 0.9689 |
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  ### Framework versions
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+ - Transformers 4.33.2
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  - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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  - Tokenizers 0.13.3