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ashhadahsan/amazon-subtheme-bert-base-finetuned
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0792
- Train Accuracy: 1.0
- Validation Loss: 2.4572
- Validation Accuracy: 0.5641
- Epoch: 12
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': 1.0, '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': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 3.5410 | 0.2497 | 3.0774 | 0.3333 | 0 |
| 2.3876 | 0.4804 | 2.5436 | 0.4103 | 1 |
| 1.5296 | 0.6930 | 2.3390 | 0.5128 | 2 |
| 1.0298 | 0.8158 | 2.3983 | 0.4615 | 3 |
| 0.7194 | 0.8971 | 2.4036 | 0.4615 | 4 |
| 0.5206 | 0.9362 | 2.4724 | 0.4359 | 5 |
| 0.3701 | 0.9669 | 2.4493 | 0.4872 | 6 |
| 0.2738 | 0.9841 | 2.3969 | 0.5641 | 7 |
| 0.2040 | 0.9929 | 2.4391 | 0.5641 | 8 |
| 0.1544 | 0.9966 | 2.4575 | 0.5641 | 9 |
| 0.1210 | 0.9993 | 2.4725 | 0.5385 | 10 |
| 0.0968 | 1.0 | 2.4445 | 0.5385 | 11 |
| 0.0792 | 1.0 | 2.4572 | 0.5641 | 12 |
Framework versions
- Transformers 4.33.0
- TensorFlow 2.12.0
- Datasets 2.1.0
- Tokenizers 0.13.3
