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oc-01-distilbert-finetuned
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: 0.0061
- Validation Loss: 0.4666
- Train Recall: 0.9070
- Epoch: 9
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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6140, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Recall | Epoch |
|---|---|---|---|
| 0.3386 | 0.2557 | 0.8915 | 0 |
| 0.1989 | 0.2661 | 0.9283 | 1 |
| 0.1097 | 0.2809 | 0.9244 | 2 |
| 0.0716 | 0.3101 | 0.9244 | 3 |
| 0.0310 | 0.4023 | 0.8721 | 4 |
| 0.0288 | 0.4877 | 0.9535 | 5 |
| 0.0155 | 0.3834 | 0.9109 | 6 |
| 0.0105 | 0.4263 | 0.9012 | 7 |
| 0.0095 | 0.4746 | 0.9070 | 8 |
| 0.0061 | 0.4666 | 0.9070 | 9 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.13.0
- Datasets 2.14.4
- Tokenizers 0.13.3
