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minhnb/ssbc_model_2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.4421
- Validation Loss: 0.7784
- Train Accuracy: 0.7046
- 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': '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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2170, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 |
|---|---|---|---|
| 1.0038 | 0.8298 | 0.6522 | 0 |
| 0.7575 | 0.7719 | 0.6774 | 1 |
| 0.6352 | 0.7647 | 0.6922 | 2 |
| 0.5380 | 0.7720 | 0.7016 | 3 |
| 0.4759 | 0.7784 | 0.7046 | 4 |
| 0.4442 | 0.7784 | 0.7046 | 5 |
| 0.4498 | 0.7784 | 0.7046 | 6 |
| 0.4444 | 0.7784 | 0.7046 | 7 |
| 0.4439 | 0.7784 | 0.7046 | 8 |
| 0.4421 | 0.7784 | 0.7046 | 9 |
Framework versions
- Transformers 4.34.1
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1
