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ratish/DBERT_CleanDesc_MAKE_v10.1
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: 0.1668
- Validation Loss: 0.7903
- Train Accuracy: 0.8
- Epoch: 14
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 |
|---|---|---|---|
| 2.2016 | 1.9470 | 0.425 | 0 |
| 1.6623 | 1.5632 | 0.575 | 1 |
| 1.2367 | 1.2743 | 0.575 | 2 |
| 0.9547 | 1.1049 | 0.75 | 3 |
| 0.7787 | 1.0268 | 0.725 | 4 |
| 0.6138 | 0.8950 | 0.75 | 5 |
| 0.5122 | 0.9161 | 0.75 | 6 |
| 0.4713 | 0.8417 | 0.8 | 7 |
| 0.4282 | 0.7698 | 0.75 | 8 |
| 0.3625 | 0.7982 | 0.75 | 9 |
| 0.2912 | 0.8342 | 0.775 | 10 |
| 0.2440 | 0.7864 | 0.775 | 11 |
| 0.2136 | 0.7688 | 0.775 | 12 |
| 0.1914 | 0.7626 | 0.8 | 13 |
| 0.1668 | 0.7903 | 0.8 | 14 |
Framework versions
- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
