Instructions to use SynchoPass/food_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SynchoPass/food_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SynchoPass/food_classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("SynchoPass/food_classifier") model = AutoModelForImageClassification.from_pretrained("SynchoPass/food_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
SynchoPass/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: 0.3965
- Validation Loss: 0.3180
- Train Accuracy: 0.926
- 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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 20000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 |
|---|---|---|---|
| 2.7774 | 1.6598 | 0.815 | 0 |
| 1.2065 | 0.7856 | 0.907 | 1 |
| 0.6840 | 0.5208 | 0.913 | 2 |
| 0.4886 | 0.4015 | 0.919 | 3 |
| 0.3965 | 0.3180 | 0.926 | 4 |
Framework versions
- Transformers 4.48.3
- TensorFlow 2.18.0
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for SynchoPass/food_classifier
Base model
google/vit-base-patch16-224-in21k