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Deexit/custom_ViT
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.9353
- Validation Loss: 1.0343
- Train Accuracy: 0.8667
- 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 1680, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Accuracy | Epoch |
|---|---|---|---|
| 2.2697 | 2.1984 | 0.4667 | 0 |
| 2.1245 | 2.0728 | 0.6 | 1 |
| 1.9780 | 1.9057 | 0.8 | 2 |
| 1.8135 | 1.7702 | 0.8667 | 3 |
| 1.6516 | 1.6121 | 0.8667 | 4 |
| 1.4854 | 1.4733 | 0.8667 | 5 |
| 1.3306 | 1.3294 | 0.8667 | 6 |
| 1.1829 | 1.2269 | 0.8333 | 7 |
| 1.0596 | 1.1176 | 0.8667 | 8 |
| 0.9353 | 1.0343 | 0.8667 | 9 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
