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End of training

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  1. README.md +10 -10
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@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4523
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- - Accuracy: 0.8126
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- - Precision: 0.6634
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- - Recall: 0.8204
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- - F1: 0.7336
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 8.743943190085984e-06
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  - train_batch_size: 32
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  - eval_batch_size: 16
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.562 | 1.0 | 243 | 0.3999 | 0.8062 | 0.6469 | 0.8449 | 0.7327 |
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- | 0.4525 | 2.0 | 486 | 0.4436 | 0.7484 | 0.5593 | 0.9429 | 0.7021 |
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- | 0.3874 | 3.0 | 729 | 0.4189 | 0.8139 | 0.6634 | 0.8286 | 0.7368 |
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- | 0.324 | 4.0 | 972 | 0.4523 | 0.8126 | 0.6634 | 0.8204 | 0.7336 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4714
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+ - Accuracy: 0.8023
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+ - Precision: 0.6350
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+ - Recall: 0.8735
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+ - F1: 0.7354
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1.669740264596789e-05
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  - train_batch_size: 32
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.5351 | 1.0 | 243 | 0.4195 | 0.8151 | 0.7095 | 0.6980 | 0.7037 |
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+ | 0.4572 | 2.0 | 486 | 0.4694 | 0.7189 | 0.5294 | 0.9551 | 0.6812 |
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+ | 0.3823 | 3.0 | 729 | 0.4196 | 0.8010 | 0.6398 | 0.8408 | 0.7266 |
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+ | 0.301 | 4.0 | 972 | 0.4714 | 0.8023 | 0.6350 | 0.8735 | 0.7354 |
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  ### Framework versions