Instructions to use Jasonnapper/my_awesome_food_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jasonnapper/my_awesome_food_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Jasonnapper/my_awesome_food_model") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Jasonnapper/my_awesome_food_model") model = AutoModelForImageClassification.from_pretrained("Jasonnapper/my_awesome_food_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
my_awesome_food_model
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:
- Loss: 0.2532
- Accuracy: 0.8867
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:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4411 | 1.0 | 41 | 0.4576 | 0.7734 |
| 0.446 | 2.0 | 82 | 0.4239 | 0.8070 |
| 0.4084 | 3.0 | 123 | 0.3635 | 0.8361 |
| 0.369 | 4.0 | 164 | 0.3487 | 0.8438 |
| 0.3624 | 5.0 | 205 | 0.3225 | 0.8668 |
| 0.3316 | 6.0 | 246 | 0.3039 | 0.8606 |
| 0.3028 | 7.0 | 287 | 0.3217 | 0.8622 |
| 0.2774 | 8.0 | 328 | 0.2996 | 0.8652 |
| 0.2831 | 9.0 | 369 | 0.2517 | 0.9020 |
| 0.2893 | 10.0 | 410 | 0.2532 | 0.8867 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.0
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Model tree for Jasonnapper/my_awesome_food_model
Base model
google/vit-base-patch16-224-in21k