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lmarchyok/e_results-5
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 2.3001
- Validation Loss: 2.1694
- 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -850, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16
Training results
Train Loss | Validation Loss | Epoch |
---|---|---|
3.1469 | 2.6912 | 0 |
2.7524 | 2.5054 | 1 |
2.6168 | 2.4093 | 2 |
2.5259 | 2.2784 | 3 |
2.4613 | 2.1857 | 4 |
2.3348 | 2.1319 | 5 |
2.2734 | 2.1327 | 6 |
2.2881 | 2.1966 | 7 |
2.2819 | 2.2081 | 8 |
2.3001 | 2.1694 | 9 |
Framework versions
- Transformers 4.26.1
- TensorFlow 2.11.0
- Datasets 2.13.1
- Tokenizers 0.13.2