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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 [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: 0.0001
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  - Precision: 1.0
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- - Recall: 1.0
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- - F1: 1.0
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- - Accuracy: 1.0
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  ## Model description
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@@ -49,42 +49,22 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 30
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  ### Training results
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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 | 6 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 |
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  | No log | 2.0 | 12 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 3.0 | 18 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 4.0 | 24 | 0.0087 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 5.0 | 30 | 0.1829 | 1.0 | 0.875 | 0.9333 | 0.9714 |
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- | No log | 6.0 | 36 | 0.0092 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 7.0 | 42 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 8.0 | 48 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 9.0 | 54 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 10.0 | 60 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 11.0 | 66 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 12.0 | 72 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 13.0 | 78 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 14.0 | 84 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 15.0 | 90 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 16.0 | 96 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 17.0 | 102 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 18.0 | 108 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 19.0 | 114 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 20.0 | 120 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 21.0 | 126 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 22.0 | 132 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 23.0 | 138 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 24.0 | 144 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 25.0 | 150 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 26.0 | 156 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 27.0 | 162 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 28.0 | 168 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 29.0 | 174 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | No log | 30.0 | 180 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
 
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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: 0.1058
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  - Precision: 1.0
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+ - Recall: 0.875
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+ - F1: 0.9333
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+ - Accuracy: 0.9714
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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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 | 6 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 |
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  | No log | 2.0 | 12 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | No log | 3.0 | 18 | 0.0344 | 1.0 | 0.875 | 0.9333 | 0.9714 |
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+ | No log | 4.0 | 24 | 0.0257 | 1.0 | 0.875 | 0.9333 | 0.9714 |
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+ | No log | 5.0 | 30 | 0.0473 | 1.0 | 0.875 | 0.9333 | 0.9714 |
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+ | No log | 6.0 | 36 | 0.0485 | 1.0 | 0.875 | 0.9333 | 0.9714 |
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+ | No log | 7.0 | 42 | 0.0581 | 1.0 | 0.875 | 0.9333 | 0.9714 |
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+ | No log | 8.0 | 48 | 0.0840 | 1.0 | 0.875 | 0.9333 | 0.9714 |
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+ | No log | 9.0 | 54 | 0.0998 | 1.0 | 0.875 | 0.9333 | 0.9714 |
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+ | No log | 10.0 | 60 | 0.1058 | 1.0 | 0.875 | 0.9333 | 0.9714 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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