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bert-salvadoran-news
This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.4210
- Validation Loss: 1.5456
- Epoch: 19
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 2.1106 | 1.9331 | 0 |
| 1.9666 | 1.7924 | 1 |
| 1.8643 | 1.7777 | 2 |
| 1.8090 | 1.7018 | 3 |
| 1.7668 | 1.7372 | 4 |
| 1.7337 | 1.6726 | 5 |
| 1.6948 | 1.6624 | 6 |
| 1.6584 | 1.6863 | 7 |
| 1.6232 | 1.6174 | 8 |
| 1.5996 | 1.6399 | 9 |
| 1.5805 | 1.5340 | 10 |
| 1.5622 | 1.6202 | 11 |
| 1.5124 | 1.6176 | 12 |
| 1.5150 | 1.5644 | 13 |
| 1.5151 | 1.6002 | 14 |
| 1.4730 | 1.5746 | 15 |
| 1.4538 | 1.5536 | 16 |
| 1.4507 | 1.5537 | 17 |
| 1.4476 | 1.5450 | 18 |
| 1.4210 | 1.5456 | 19 |
Framework versions
- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.7.1
- Tokenizers 0.13.2
