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# food_classifier_2025_03_18_20_39

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5122
- Accuracy: 0.8746

## 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: 0.0006
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 2048
- total_eval_batch_size: 512
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 18

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9399        | 1.0   | 37   | 3.1445          | 0.7088   |
| 1.578         | 2.0   | 74   | 1.1087          | 0.7971   |
| 0.9126        | 3.0   | 111  | 0.7459          | 0.8190   |
| 0.7204        | 4.0   | 148  | 0.6649          | 0.8352   |
| 0.611         | 5.0   | 185  | 0.6167          | 0.8424   |
| 0.5583        | 6.0   | 222  | 0.5946          | 0.8468   |
| 0.4702        | 7.0   | 259  | 0.5649          | 0.8561   |
| 0.4427        | 8.0   | 296  | 0.5751          | 0.8512   |
| 0.3757        | 9.0   | 333  | 0.5720          | 0.8535   |
| 0.3356        | 10.0  | 370  | 0.5514          | 0.8589   |
| 0.3129        | 11.0  | 407  | 0.5458          | 0.8612   |
| 0.2894        | 12.0  | 444  | 0.5399          | 0.8595   |
| 0.2513        | 13.0  | 481  | 0.5293          | 0.8675   |
| 0.2419        | 14.0  | 518  | 0.5299          | 0.868    |
| 0.2137        | 15.0  | 555  | 0.5250          | 0.8703   |
| 0.2215        | 16.0  | 592  | 0.5194          | 0.8676   |
| 0.2046        | 17.0  | 629  | 0.5201          | 0.8689   |
| 0.1864        | 18.0  | 666  | 0.5122          | 0.8746   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0

apple_pie baby_back_ribs bruschetta waffles caesar_salad cannoli caprese_salad carrot_cake ceviche cheesecake cheese_plate chicken_curry chicken_quesadilla baklava chicken_wings chocolate_cake chocolate_mousse churros clam_chowder club_sandwich crab_cakes creme_brulee croque_madame cup_cakes beef_carpaccio deviled_eggs donuts dumplings edamame eggs_benedict escargots falafel filet_mignon fish_and_chips foie_gras beef_tartare french_fries french_onion_soup french_toast fried_calamari fried_rice frozen_yogurt garlic_bread gnocchi greek_salad grilled_cheese_sandwich beet_salad grilled_salmon guacamole gyoza hamburger hot_and_sour_soup hot_dog huevos_rancheros hummus ice_cream lasagna beignets lobster_bisque lobster_roll_sandwich macaroni_and_cheese macarons miso_soup mussels nachos omelette onion_rings oysters bibimbap pad_thai paella pancakes panna_cotta peking_duck pho pizza pork_chop poutine prime_rib bread_pudding pulled_pork_sandwich ramen ravioli red_velvet_cake risotto samosa sashimi scallops seaweed_salad shrimp_and_grits breakfast_burrito spaghetti_bolognese spaghetti_carbonara spring_rolls steak strawberry_shortcake sushi tacos takoyaki tiramisu tuna_tartare