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shbA/food_classifier
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: 0.6730
- Train Accuracy: 0.675
- Validation Loss: 0.6380
- Validation Accuracy: 0.8000
- Epoch: 5
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': 1600, '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': 0.05}
- training_precision: float32
Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|---|---|---|---|---|
| 0.8438 | 0.625 | 0.6171 | 0.8000 | 0 |
| 0.9123 | 0.625 | 0.8710 | 0.6000 | 1 |
| 0.7847 | 0.7 | 0.5295 | 1.0 | 2 |
| 0.8369 | 0.625 | 0.5829 | 1.0 | 3 |
| 0.7734 | 0.675 | 1.0318 | 0.4000 | 4 |
| 0.6730 | 0.675 | 0.6380 | 0.8000 | 5 |
Framework versions
- Transformers 4.29.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
