<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. -->
cc-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: 0.0271
- Validation Loss: 0.5850
- Train Recall: 0.8092
- 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', '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': 1760, '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 |
|---|---|---|---|
| 0.5148 | 0.4230 | 0.6776 | 0 |
| 0.3028 | 0.3672 | 0.7961 | 1 |
| 0.1848 | 0.3852 | 0.8355 | 2 |
| 0.0993 | 0.5016 | 0.7434 | 3 |
| 0.0604 | 0.4713 | 0.8684 | 4 |
| 0.0271 | 0.5850 | 0.8092 | 5 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.13.0
- Datasets 2.14.4
- Tokenizers 0.13.3
