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vjsyong/xlm-roberta-dementia_detection
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0140
- Validation Loss: 0.4773
- Train Accuracy: 0.8958
- Epoch: 13
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': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 378, '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}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|---|---|---|---|
| 0.1762 | 0.3984 | 0.875 | 0 |
| 0.1873 | 0.3250 | 0.8542 | 1 |
| 0.1339 | 0.4448 | 0.875 | 2 |
| 0.0316 | 0.4015 | 0.8958 | 3 |
| 0.0226 | 0.4410 | 0.875 | 4 |
| 0.0166 | 0.4586 | 0.8958 | 5 |
| 0.0157 | 0.4710 | 0.8958 | 6 |
| 0.0113 | 0.4772 | 0.8958 | 7 |
| 0.0159 | 0.4773 | 0.8958 | 8 |
| 0.0105 | 0.4773 | 0.8958 | 9 |
| 0.0119 | 0.4773 | 0.8958 | 10 |
| 0.0120 | 0.4773 | 0.8958 | 11 |
| 0.0135 | 0.4773 | 0.8958 | 12 |
| 0.0140 | 0.4773 | 0.8958 | 13 |
Framework versions
- Transformers 4.28.1
- TensorFlow 2.10.1
- Datasets 2.11.0
- Tokenizers 0.13.3
