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LovenOO/distilBERT_without_preprocessing
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: 0.1466
- Validation Loss: 0.3625
- Train Precision: 0.8491
- Train Recall: 0.8642
- Train F1: 0.8544
- Train Accuracy: 0.8906
- Epoch: 5
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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2565, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|---|---|---|---|---|---|---|
| 0.8177 | 0.4723 | 0.8407 | 0.7879 | 0.7948 | 0.8575 | 0 |
| 0.3642 | 0.3777 | 0.8666 | 0.8315 | 0.8465 | 0.8847 | 1 |
| 0.2734 | 0.3804 | 0.8466 | 0.8563 | 0.8471 | 0.8872 | 2 |
| 0.2020 | 0.3704 | 0.8526 | 0.8663 | 0.8551 | 0.8896 | 3 |
| 0.1638 | 0.3625 | 0.8491 | 0.8642 | 0.8544 | 0.8906 | 4 |
| 0.1466 | 0.3625 | 0.8491 | 0.8642 | 0.8544 | 0.8906 | 5 |
Framework versions
- Transformers 4.24.0
- TensorFlow 2.13.0
- Datasets 2.14.2
- Tokenizers 0.11.0
