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HASAN55/bert-finetuned-for-distil
This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.8322
- Train End Logits Accuracy: 0.7636
- Train Start Logits Accuracy: 0.7311
- Validation Loss: 1.1398
- Validation End Logits Accuracy: 0.7014
- Validation Start Logits Accuracy: 0.6678
- Epoch: 3
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': 1e-05, 'decay_steps': 25124, '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': 0.001}
- training_precision: mixed_float16
Training results
| Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 1.7468 | 0.5488 | 0.5204 | 1.2282 | 0.6706 | 0.6367 | 0 |
| 1.1198 | 0.6922 | 0.6597 | 1.1548 | 0.6880 | 0.6558 | 1 |
| 0.9378 | 0.7370 | 0.7038 | 1.1243 | 0.6965 | 0.6631 | 2 |
| 0.8322 | 0.7636 | 0.7311 | 1.1398 | 0.7014 | 0.6678 | 3 |
Framework versions
- Transformers 4.27.4
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.3
