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roberta-bne-fine-tuned-text-classification-SL-data-augmentation-dss
This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3544
- F1: 0.4643
- Recall: 0.4629
- Accuracy: 0.4629
- Precision: 0.4880
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | Precision |
|---|---|---|---|---|---|---|---|
| 3.3244 | 1.0 | 562 | 2.7345 | 0.3306 | 0.3939 | 0.3939 | 0.3500 |
| 2.4396 | 2.0 | 1124 | 2.4186 | 0.4061 | 0.4468 | 0.4468 | 0.4349 |
| 1.8841 | 3.0 | 1686 | 2.2738 | 0.4453 | 0.4702 | 0.4702 | 0.4583 |
| 1.4409 | 4.0 | 2248 | 2.2984 | 0.4500 | 0.4582 | 0.4582 | 0.4625 |
| 1.0328 | 5.0 | 2810 | 2.3544 | 0.4643 | 0.4629 | 0.4629 | 0.4880 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
