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End of training

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README.md CHANGED
@@ -18,9 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8207
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- - Accuracy: 0.702
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- - F1: 0.7806
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  ## Model description
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@@ -40,25 +40,20 @@ More information needed
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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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- - num_epochs: 8
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.6404 | 1.0 | 751 | 0.5949 | 0.739 | 0.8065 |
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- | 0.6075 | 2.0 | 1502 | 0.5335 | 0.758 | 0.8296 |
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- | 0.5722 | 3.0 | 2253 | 0.5041 | 0.777 | 0.8327 |
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- | 0.539 | 4.0 | 3004 | 0.5608 | 0.744 | 0.8158 |
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- | 0.4922 | 5.0 | 3755 | 0.6350 | 0.711 | 0.7765 |
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- | 0.4296 | 6.0 | 4506 | 0.6518 | 0.732 | 0.7938 |
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- | 0.3761 | 7.0 | 5257 | 0.7428 | 0.711 | 0.7864 |
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- | 0.3356 | 8.0 | 6008 | 0.8207 | 0.702 | 0.7806 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6567
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+ - Accuracy: 0.735
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+ - F1: 0.8030
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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: 4
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+ - eval_batch_size: 4
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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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.6079 | 1.0 | 1502 | 0.5489 | 0.72 | 0.7764 |
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+ | 0.5703 | 2.0 | 3004 | 0.5609 | 0.74 | 0.8110 |
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+ | 0.5169 | 3.0 | 4506 | 0.6567 | 0.735 | 0.8030 |
 
 
 
 
 
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  ### Framework versions
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