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ratish/DBERT_CleanDesc_v1
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: 0.3845
- Validation Loss: 0.8665
- Train Accuracy: 0.75
- Epoch: 7
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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3090, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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 Accuracy | Epoch |
|---|---|---|---|
| 2.2264 | 2.0161 | 0.425 | 0 |
| 1.7311 | 1.6541 | 0.6 | 1 |
| 1.3066 | 1.3472 | 0.6 | 2 |
| 0.9729 | 1.1490 | 0.65 | 3 |
| 0.7551 | 1.0330 | 0.725 | 4 |
| 0.5916 | 0.9158 | 0.725 | 5 |
| 0.4522 | 0.8656 | 0.725 | 6 |
| 0.3845 | 0.8665 | 0.75 | 7 |
Framework versions
- Transformers 4.27.4
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.3
