AIYIYA/my_wr
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: 1.3017
- Validation Loss: 1.2447
- Train Accuracy: 0.7895
- Epoch: 7
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': 120, '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 |
---|---|---|---|
2.8885 | 2.6740 | 0.1316 | 0 |
2.5028 | 2.3158 | 0.4737 | 1 |
2.2462 | 2.0331 | 0.6579 | 2 |
1.9850 | 1.7608 | 0.7632 | 3 |
1.7761 | 1.6215 | 0.7632 | 4 |
1.6159 | 1.4274 | 0.7895 | 5 |
1.3905 | 1.3232 | 0.7895 | 6 |
1.3017 | 1.2447 | 0.7895 | 7 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
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Base model
google-bert/bert-base-chinese