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cruiser/final_model
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: 0.0316
- Validation Loss: 1.1405
- Train Accuracy: 0.7835
- Epoch: 10
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': 'WarmUp', 'config': {'initial_learning_rate': 1e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 34090, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 250, 'power': 1.0, '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 |
|---|---|---|---|
| 0.6358 | 0.5405 | 0.7821 | 0 |
| 0.4380 | 0.5118 | 0.7844 | 1 |
| 0.3382 | 0.5437 | 0.7960 | 2 |
| 0.2327 | 0.6227 | 0.7878 | 3 |
| 0.1581 | 0.7234 | 0.7795 | 4 |
| 0.1104 | 0.8340 | 0.7832 | 5 |
| 0.0826 | 0.8824 | 0.7778 | 6 |
| 0.0608 | 1.0342 | 0.7827 | 7 |
| 0.0456 | 1.0815 | 0.7818 | 8 |
| 0.0396 | 1.0829 | 0.7852 | 9 |
| 0.0316 | 1.1405 | 0.7835 | 10 |
Framework versions
- Transformers 4.27.4
- TensorFlow 2.11.0
- Datasets 2.1.0
- Tokenizers 0.13.2
