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bertin-roberta-fine-tuned-text-classification-SL-data-augmentation-test
This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7374
- F1: 0.1580
- Recall: 0.3233
- Accuracy: 0.3233
- Precision: 0.1045
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: 0.0001
- 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 |
|---|---|---|---|---|---|---|---|
| 2.7132 | 1.0 | 6530 | 2.7463 | 0.1580 | 0.3233 | 0.3233 | 0.1045 |
| 2.7441 | 2.0 | 13060 | 2.7423 | 0.1580 | 0.3233 | 0.3233 | 0.1045 |
| 2.7328 | 3.0 | 19590 | 2.7365 | 0.1580 | 0.3233 | 0.3233 | 0.1045 |
| 2.7464 | 4.0 | 26120 | 2.7374 | 0.1580 | 0.3233 | 0.3233 | 0.1045 |
| 2.7178 | 5.0 | 32650 | 2.7374 | 0.1580 | 0.3233 | 0.3233 | 0.1045 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
