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ratish/DBERT_MAKE_NewData_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: 0.5238
- Validation Loss: 0.6256
- Train Accuracy: 0.8909
- 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': 240, '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 |
|---|---|---|---|
| 2.2333 | 1.9085 | 0.6545 | 0 |
| 1.6567 | 1.3839 | 0.6727 | 1 |
| 1.2308 | 1.0679 | 0.8364 | 2 |
| 0.9605 | 0.8879 | 0.8364 | 3 |
| 0.8155 | 0.7807 | 0.8364 | 4 |
| 0.7106 | 0.7242 | 0.8545 | 5 |
| 0.6365 | 0.6794 | 0.8182 | 6 |
| 0.5894 | 0.6334 | 0.8909 | 7 |
| 0.5446 | 0.6293 | 0.8909 | 8 |
| 0.5238 | 0.6256 | 0.8909 | 9 |
Framework versions
- Transformers 4.28.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
