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ratish/DBERT_CleanDesc_Collision_v2.5
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: 0.4855
- Validation Loss: 1.0752
- Train Accuracy: 0.6410
- 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3040, '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 |
|---|---|---|---|
| 1.5849 | 1.6211 | 0.3333 | 0 |
| 1.4751 | 1.5922 | 0.3333 | 1 |
| 1.3947 | 1.4869 | 0.4359 | 2 |
| 1.2663 | 1.3455 | 0.5641 | 3 |
| 1.0385 | 1.2647 | 0.5897 | 4 |
| 0.9351 | 1.2546 | 0.5897 | 5 |
| 0.8036 | 1.2566 | 0.5897 | 6 |
| 0.7181 | 1.1101 | 0.6154 | 7 |
| 0.6027 | 1.1042 | 0.6410 | 8 |
| 0.4855 | 1.0752 | 0.6410 | 9 |
Framework versions
- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.3
