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@@ -24,52 +24,4 @@ It achieves the following results on the evaluation set:
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  - Precision: 0.5070
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  - Recall: 0.5725
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  - F1: 0.5377
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- - Accuracy: 0.7903
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- ## Model description
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- More information needed
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- ## Intended uses & limitations
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- More information needed
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- ## Training and evaluation data
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- More information needed
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- ## Training procedure
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- ### Training hyperparameters
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- The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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: cosine
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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 | 45 | 1.5295 | 0.2627 | 0.0223 | 0.0411 | 0.6639 |
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- | No log | 2.0 | 90 | 1.2463 | 0.3241 | 0.2831 | 0.3022 | 0.6845 |
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- | No log | 3.0 | 135 | 1.0915 | 0.3560 | 0.4052 | 0.3790 | 0.7005 |
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- | No log | 4.0 | 180 | 0.9411 | 0.5225 | 0.3180 | 0.3954 | 0.7428 |
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- | No log | 5.0 | 225 | 0.8653 | 0.4437 | 0.5304 | 0.4832 | 0.7580 |
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- | No log | 6.0 | 270 | 0.7936 | 0.4913 | 0.5362 | 0.5128 | 0.7798 |
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- | No log | 7.0 | 315 | 0.7715 | 0.4974 | 0.5623 | 0.5279 | 0.7840 |
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- | No log | 8.0 | 360 | 0.7545 | 0.5083 | 0.5601 | 0.5329 | 0.7880 |
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- | No log | 9.0 | 405 | 0.7464 | 0.5125 | 0.5694 | 0.5395 | 0.7921 |
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- | No log | 10.0 | 450 | 0.7475 | 0.5070 | 0.5725 | 0.5377 | 0.7903 |
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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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  - Precision: 0.5070
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  - Recall: 0.5725
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  - F1: 0.5377
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+ - Accuracy: 0.7903