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bertbaseuncasedny
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.3901
- Train End Logits Accuracy: 0.8823
- Train Start Logits Accuracy: 0.8513
- Validation Loss: 1.2123
- Validation End Logits Accuracy: 0.7291
- Validation Start Logits Accuracy: 0.6977
- 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': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 29508, '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 | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 1.2597 | 0.6683 | 0.6277 | 1.0151 | 0.7214 | 0.6860 | 0 |
| 0.7699 | 0.7820 | 0.7427 | 1.0062 | 0.7342 | 0.6996 | 1 |
| 0.5343 | 0.8425 | 0.8064 | 1.1162 | 0.7321 | 0.7010 | 2 |
| 0.3901 | 0.8823 | 0.8513 | 1.2123 | 0.7291 | 0.6977 | 3 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.6.4
- Datasets 2.1.0
- Tokenizers 0.12.1
