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andreiliphdpr/distilbert-base-uncased-finetuned-cola
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: 0.0015
- Train Accuracy: 0.9995
- Validation Loss: 0.0570
- Validation Accuracy: 0.9915
- Epoch: 4
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': 43750, '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 Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 0.0399 | 0.9870 | 0.0281 | 0.9908 | 0 |
| 0.0182 | 0.9944 | 0.0326 | 0.9901 | 1 |
| 0.0089 | 0.9971 | 0.0396 | 0.9912 | 2 |
| 0.0040 | 0.9987 | 0.0486 | 0.9918 | 3 |
| 0.0015 | 0.9995 | 0.0570 | 0.9915 | 4 |
Framework versions
- Transformers 4.15.0.dev0
- TensorFlow 2.6.2
- Datasets 1.15.1
- Tokenizers 0.10.3
