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vc-01-bert-finetuned
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: 0.0074
- Validation Loss: 0.4494
- Train Recall: 0.9247
- Epoch: 8
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': 7920, '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 |
|---|---|---|---|
| 0.3152 | 0.3003 | 0.9383 | 0 |
| 0.1993 | 0.2504 | 0.9036 | 1 |
| 0.1250 | 0.2717 | 0.9232 | 2 |
| 0.0654 | 0.3074 | 0.8870 | 3 |
| 0.0347 | 0.3127 | 0.9232 | 4 |
| 0.0268 | 0.4317 | 0.9217 | 5 |
| 0.0146 | 0.4449 | 0.9066 | 6 |
| 0.0092 | 0.4419 | 0.9066 | 7 |
| 0.0074 | 0.4494 | 0.9247 | 8 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.13.0
- Datasets 2.14.4
- Tokenizers 0.13.3
