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# food_vit_model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the food101 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5959
- Accuracy: 0.8749

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4008        | 1.0   | 592   | 0.5106          | 0.8690   |
| 0.313         | 2.0   | 1184  | 0.5045          | 0.8718   |
| 0.3444        | 3.0   | 1776  | 0.5029          | 0.8711   |
| 0.3305        | 4.0   | 2368  | 0.5049          | 0.8706   |
| 0.2993        | 5.0   | 2960  | 0.5123          | 0.8702   |
| 0.3658        | 6.0   | 3552  | 0.5202          | 0.8662   |
| 0.314         | 7.0   | 4144  | 0.5344          | 0.8633   |
| 0.2973        | 8.0   | 4736  | 0.5558          | 0.8589   |
| 0.3171        | 9.0   | 5328  | 0.5806          | 0.8566   |
| 0.2841        | 10.0  | 5920  | 0.5932          | 0.856    |
| 0.4034        | 11.0  | 6512  | 0.5770          | 0.8554   |
| 0.3231        | 12.0  | 7104  | 0.5455          | 0.8607   |
| 0.3162        | 13.0  | 7696  | 0.5420          | 0.8634   |
| 0.3706        | 14.0  | 8288  | 0.5591          | 0.8590   |
| 0.2857        | 15.0  | 8880  | 0.5284          | 0.8653   |
| 0.2647        | 16.0  | 9472  | 0.5680          | 0.8567   |
| 0.2411        | 17.0  | 10064 | 0.5492          | 0.8648   |
| 0.2566        | 18.0  | 10656 | 0.5716          | 0.8581   |
| 0.2338        | 19.0  | 11248 | 0.5842          | 0.8573   |
| 0.2862        | 20.0  | 11840 | 0.5735          | 0.8592   |
| 0.2689        | 21.0  | 12432 | 0.5669          | 0.8604   |
| 0.1892        | 22.0  | 13024 | 0.5747          | 0.8602   |
| 0.1801        | 23.0  | 13616 | 0.5581          | 0.8627   |
| 0.2258        | 24.0  | 14208 | 0.5717          | 0.8614   |
| 0.2215        | 25.0  | 14800 | 0.6046          | 0.8562   |
| 0.1443        | 26.0  | 15392 | 0.5758          | 0.8642   |
| 0.2143        | 27.0  | 15984 | 0.5805          | 0.8626   |
| 0.1699        | 28.0  | 16576 | 0.5843          | 0.8616   |
| 0.1787        | 29.0  | 17168 | 0.5740          | 0.8657   |
| 0.1702        | 30.0  | 17760 | 0.5718          | 0.8653   |
| 0.1703        | 31.0  | 18352 | 0.5703          | 0.8646   |
| 0.1692        | 32.0  | 18944 | 0.5918          | 0.8627   |
| 0.1643        | 33.0  | 19536 | 0.6041          | 0.8608   |
| 0.214         | 34.0  | 20128 | 0.5950          | 0.8624   |
| 0.1996        | 35.0  | 20720 | 0.5861          | 0.8637   |
| 0.1618        | 36.0  | 21312 | 0.6032          | 0.8622   |
| 0.181         | 37.0  | 21904 | 0.5915          | 0.8646   |
| 0.1641        | 38.0  | 22496 | 0.5697          | 0.8663   |
| 0.1233        | 39.0  | 23088 | 0.5987          | 0.8617   |
| 0.1469        | 40.0  | 23680 | 0.5944          | 0.8635   |
| 0.1492        | 41.0  | 24272 | 0.5893          | 0.8651   |
| 0.1616        | 42.0  | 24864 | 0.5717          | 0.8667   |
| 0.1359        | 43.0  | 25456 | 0.5897          | 0.8655   |
| 0.1318        | 44.0  | 26048 | 0.5920          | 0.8684   |
| 0.102         | 45.0  | 26640 | 0.5908          | 0.8683   |
| 0.1416        | 46.0  | 27232 | 0.5977          | 0.8625   |
| 0.1393        | 47.0  | 27824 | 0.6069          | 0.8648   |
| 0.1003        | 48.0  | 28416 | 0.5849          | 0.8682   |
| 0.121         | 49.0  | 29008 | 0.5880          | 0.8661   |
| 0.128         | 50.0  | 29600 | 0.5800          | 0.8693   |
| 0.1409        | 51.0  | 30192 | 0.6004          | 0.8663   |
| 0.1783        | 52.0  | 30784 | 0.5847          | 0.8678   |
| 0.1177        | 53.0  | 31376 | 0.5984          | 0.8683   |
| 0.097         | 54.0  | 31968 | 0.5973          | 0.8669   |
| 0.137         | 55.0  | 32560 | 0.5983          | 0.8668   |
| 0.1227        | 56.0  | 33152 | 0.5913          | 0.8689   |
| 0.1259        | 57.0  | 33744 | 0.5949          | 0.868    |
| 0.0947        | 58.0  | 34336 | 0.6065          | 0.8664   |
| 0.1184        | 59.0  | 34928 | 0.6098          | 0.8667   |
| 0.0996        | 60.0  | 35520 | 0.5958          | 0.8700   |
| 0.0977        | 61.0  | 36112 | 0.6019          | 0.8694   |
| 0.1295        | 62.0  | 36704 | 0.6012          | 0.8698   |
| 0.0842        | 63.0  | 37296 | 0.5993          | 0.8688   |
| 0.0784        | 64.0  | 37888 | 0.6074          | 0.8689   |
| 0.1183        | 65.0  | 38480 | 0.5853          | 0.8713   |
| 0.1215        | 66.0  | 39072 | 0.5962          | 0.8709   |
| 0.1069        | 67.0  | 39664 | 0.5786          | 0.8728   |
| 0.101         | 68.0  | 40256 | 0.5938          | 0.8691   |
| 0.1004        | 69.0  | 40848 | 0.5985          | 0.8716   |
| 0.0958        | 70.0  | 41440 | 0.5961          | 0.8721   |
| 0.0914        | 71.0  | 42032 | 0.6053          | 0.8704   |
| 0.0915        | 72.0  | 42624 | 0.5937          | 0.8713   |
| 0.0964        | 73.0  | 43216 | 0.6001          | 0.8703   |
| 0.0558        | 74.0  | 43808 | 0.5993          | 0.8697   |
| 0.0977        | 75.0  | 44400 | 0.6025          | 0.8706   |
| 0.1096        | 76.0  | 44992 | 0.6018          | 0.8706   |
| 0.0883        | 77.0  | 45584 | 0.5973          | 0.8733   |
| 0.0811        | 78.0  | 46176 | 0.6023          | 0.8741   |
| 0.0912        | 79.0  | 46768 | 0.6004          | 0.8733   |
| 0.0981        | 80.0  | 47360 | 0.5851          | 0.8730   |
| 0.0892        | 81.0  | 47952 | 0.5782          | 0.8754   |
| 0.1119        | 82.0  | 48544 | 0.5893          | 0.8727   |
| 0.1016        | 83.0  | 49136 | 0.5911          | 0.8722   |
| 0.0801        | 84.0  | 49728 | 0.5880          | 0.8755   |
| 0.107         | 85.0  | 50320 | 0.6088          | 0.8710   |
| 0.0763        | 86.0  | 50912 | 0.5912          | 0.8760   |
| 0.0667        | 87.0  | 51504 | 0.5974          | 0.8752   |
| 0.0485        | 88.0  | 52096 | 0.5903          | 0.8763   |
| 0.1002        | 89.0  | 52688 | 0.6097          | 0.8744   |
| 0.0786        | 90.0  | 53280 | 0.5853          | 0.8762   |
| 0.1067        | 91.0  | 53872 | 0.5874          | 0.8772   |
| 0.0618        | 92.0  | 54464 | 0.5847          | 0.8762   |
| 0.0667        | 93.0  | 55056 | 0.5803          | 0.8774   |
| 0.0702        | 94.0  | 55648 | 0.5812          | 0.8781   |
| 0.055         | 95.0  | 56240 | 0.5918          | 0.8761   |
| 0.0941        | 96.0  | 56832 | 0.5904          | 0.8766   |
| 0.0821        | 97.0  | 57424 | 0.5849          | 0.8762   |
| 0.0998        | 98.0  | 58016 | 0.5891          | 0.8757   |
| 0.0594        | 99.0  | 58608 | 0.5845          | 0.8778   |
| 0.0727        | 100.0 | 59200 | 0.5959          | 0.8749   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3

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