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mbordes/masked-lm-tpu
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 9.8611
- Train Accuracy: 0.0090
- Validation Loss: 9.7448
- Validation Accuracy: 0.0214
- Epoch: 8
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': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 22325, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 1175, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 10.1794 | 0.0 | 10.1765 | 0.0 | 0 |
| 10.1802 | 0.0 | 10.1664 | 0.0 | 1 |
| 10.1601 | 0.0 | 10.1314 | 0.0 | 2 |
| 10.1402 | 0.0 | 10.0929 | 0.0000 | 3 |
| 10.0994 | 0.0000 | 10.0454 | 0.0000 | 4 |
| 10.0484 | 0.0000 | 9.9790 | 0.0003 | 5 |
| 9.9974 | 0.0003 | 9.9065 | 0.0025 | 6 |
| 9.9256 | 0.0023 | 9.8325 | 0.0130 | 7 |
| 9.8611 | 0.0090 | 9.7448 | 0.0214 | 8 |
Framework versions
- Transformers 4.33.1
- TensorFlow 2.12.0
- Tokenizers 0.13.3
