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wine-reviews-roberta
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: 0.2715
- Train Acc: 0.8906
- Validation Loss: 0.6536
- Validation Acc: 0.7701
- Epoch: 4
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': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 24455, '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 | Train Acc | Validation Loss | Validation Acc | Epoch |
|---|---|---|---|---|
| 0.6164 | 0.7297 | 0.5360 | 0.7665 | 0 |
| 0.5040 | 0.7820 | 0.5145 | 0.7739 | 1 |
| 0.4248 | 0.8206 | 0.5470 | 0.7744 | 2 |
| 0.3413 | 0.8583 | 0.6132 | 0.7699 | 3 |
| 0.2715 | 0.8906 | 0.6536 | 0.7701 | 4 |
Framework versions
- Transformers 4.28.1
- TensorFlow 2.11.0
- Datasets 2.1.0
- Tokenizers 0.13.3
