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End of training

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README.md CHANGED
@@ -14,11 +14,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # roberta-large-Dep-first
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- This model is a fine-tuned version of [ericNguyen0132/roberta-large-Dep-pretrain](https://huggingface.co/ericNguyen0132/roberta-large-Dep-pretrain) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6367
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- - Accuracy: 0.689
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- - F1: 0.3792
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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- - train_batch_size: 9
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- - eval_batch_size: 9
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.6476 | 1.0 | 668 | 0.6363 | 0.682 | 0.3484 |
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- | 0.6156 | 2.0 | 1336 | 0.6510 | 0.678 | 0.3374 |
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- | 0.6184 | 3.0 | 2004 | 0.6436 | 0.678 | 0.3347 |
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- | 0.613 | 4.0 | 2672 | 0.6354 | 0.686 | 0.3669 |
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- | 0.596 | 5.0 | 3340 | 0.6367 | 0.689 | 0.3792 |
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  ### Framework versions
 
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  # roberta-large-Dep-first
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+ This model is a fine-tuned version of [rafalposwiata/deproberta-large-depression](https://huggingface.co/rafalposwiata/deproberta-large-depression) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1795
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+ - Accuracy: 0.702
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+ - F1: 0.5706
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-06
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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: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.5563 | 1.0 | 751 | 0.5324 | 0.756 | 0.6188 |
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+ | 0.4721 | 2.0 | 1502 | 0.6204 | 0.691 | 0.5874 |
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+ | 0.3836 | 3.0 | 2253 | 0.7990 | 0.696 | 0.525 |
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+ | 0.3245 | 4.0 | 3004 | 0.9714 | 0.694 | 0.5726 |
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+ | 0.2795 | 5.0 | 3755 | 1.1795 | 0.702 | 0.5706 |
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  ### Framework versions
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