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jborras18/my_awesome_wnut_model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0263
- Validation Loss: 0.0494
- Train Precision: 0.9307
- Train Recall: 0.9404
- Train F1: 0.9355
- Train Accuracy: 0.9873
- Epoch: 2
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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2631, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 0.1774 | 0.0563 | 0.9129 | 0.9228 | 0.9178 | 0.9846 | 0 |
| 0.0427 | 0.0490 | 0.9218 | 0.9364 | 0.9290 | 0.9866 | 1 |
| 0.0263 | 0.0494 | 0.9307 | 0.9404 | 0.9355 | 0.9873 | 2 |
Framework versions
- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.9.0
- Tokenizers 0.13.2
