CynthiaCR/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: 0.5354
- Validation Loss: 1.3575
- Train Accuracy: 0.5062
- 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': 6400, '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 |
---|---|---|---|
2.0502 | 2.0061 | 0.2375 | 0 |
1.8368 | 1.7539 | 0.3187 | 1 |
1.6074 | 1.6316 | 0.3875 | 2 |
1.4768 | 1.5368 | 0.4437 | 3 |
1.3390 | 1.4388 | 0.4813 | 4 |
1.1889 | 1.3995 | 0.4562 | 5 |
1.0397 | 1.3773 | 0.4688 | 6 |
0.8703 | 1.4785 | 0.4625 | 7 |
0.6962 | 1.3854 | 0.4938 | 8 |
0.5354 | 1.3575 | 0.5062 | 9 |
Framework versions
- Transformers 4.29.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3
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