Training in progress, epoch 1
Browse files
README.md
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This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- F1-score: 0.
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- Precision: 0.
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- Recall: 0.
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- Auc: 0.
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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:
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- train_batch_size:
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- eval_batch_size:
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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-score | Precision | Recall | Auc |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
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| 0.
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| 0.
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### Framework versions
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This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3567
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- Accuracy: 0.8396
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- F1-score: 0.7752
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- Precision: 0.7713
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- Recall: 0.7794
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- Auc: 0.7794
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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: 3e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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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-score | Precision | Recall | Auc |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
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| 0.4074 | 1.0 | 39 | 0.3802 | 0.8347 | 0.7643 | 0.7649 | 0.7636 | 0.7636 |
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| 0.297 | 2.0 | 78 | 0.3567 | 0.8396 | 0.7752 | 0.7713 | 0.7794 | 0.7794 |
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### Framework versions
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model.safetensors
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training_args.bin
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