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AIYIYA/my_12
This model is a fine-tuned version of bert-base-chinese on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.5441
- Validation Loss: 1.0817
- Train Accuracy: 0.7799
- Epoch: 11
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 580, '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 |
|---|---|---|---|
| 3.3278 | 2.9680 | 0.3208 | 0 |
| 2.7007 | 2.5022 | 0.4654 | 1 |
| 2.1853 | 2.0269 | 0.5597 | 2 |
| 1.7380 | 1.7066 | 0.6352 | 3 |
| 1.4422 | 1.5095 | 0.6855 | 4 |
| 1.1789 | 1.3789 | 0.7484 | 5 |
| 1.0105 | 1.3038 | 0.7484 | 6 |
| 0.8728 | 1.2295 | 0.7484 | 7 |
| 0.7790 | 1.1804 | 0.7484 | 8 |
| 0.6699 | 1.1553 | 0.7673 | 9 |
| 0.6131 | 1.1061 | 0.7673 | 10 |
| 0.5441 | 1.0817 | 0.7799 | 11 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.13.1
- Tokenizers 0.13.3
