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# finetuned-food101

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: 0.6105
- Accuracy: 0.8400

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 4.1344        | 0.0248 | 100   | 4.0304          | 0.3063   |
| 3.5328        | 0.0497 | 200   | 3.3729          | 0.4410   |
| 2.9715        | 0.0745 | 300   | 2.8900          | 0.5135   |
| 2.724         | 0.0994 | 400   | 2.5096          | 0.5443   |
| 2.311         | 0.1242 | 500   | 2.1726          | 0.5895   |
| 2.266         | 0.1491 | 600   | 2.0223          | 0.5880   |
| 1.9671        | 0.1739 | 700   | 1.7585          | 0.6330   |
| 1.8617        | 0.1988 | 800   | 1.7300          | 0.6212   |
| 1.4694        | 0.2236 | 900   | 1.7507          | 0.6078   |
| 1.7876        | 0.2484 | 1000  | 1.6520          | 0.6133   |
| 1.7647        | 0.2733 | 1100  | 1.4576          | 0.6598   |
| 1.7           | 0.2981 | 1200  | 1.4420          | 0.6577   |
| 1.533         | 0.3230 | 1300  | 1.4389          | 0.6537   |
| 1.3895        | 0.3478 | 1400  | 1.4178          | 0.6587   |
| 1.5497        | 0.3727 | 1500  | 1.3048          | 0.6861   |
| 1.3327        | 0.3975 | 1600  | 1.3361          | 0.6714   |
| 1.53          | 0.4224 | 1700  | 1.3425          | 0.6697   |
| 1.538         | 0.4472 | 1800  | 1.3453          | 0.6642   |
| 1.5056        | 0.4720 | 1900  | 1.2742          | 0.6783   |
| 1.2728        | 0.4969 | 2000  | 1.1779          | 0.7045   |
| 1.1734        | 0.5217 | 2100  | 1.2630          | 0.6808   |
| 1.527         | 0.5466 | 2200  | 1.1810          | 0.7023   |
| 1.3873        | 0.5714 | 2300  | 1.1831          | 0.7040   |
| 1.3545        | 0.5963 | 2400  | 1.1836          | 0.7002   |
| 1.4842        | 0.6211 | 2500  | 1.1441          | 0.7129   |
| 1.1974        | 0.6460 | 2600  | 1.1230          | 0.7155   |
| 1.4204        | 0.6708 | 2700  | 1.1766          | 0.7002   |
| 1.152         | 0.6957 | 2800  | 1.2166          | 0.6950   |
| 1.162         | 0.7205 | 2900  | 1.1674          | 0.7003   |
| 1.4516        | 0.7453 | 3000  | 1.1207          | 0.7140   |
| 1.2378        | 0.7702 | 3100  | 1.2072          | 0.6906   |
| 0.991         | 0.7950 | 3200  | 1.1122          | 0.7131   |
| 1.3078        | 0.8199 | 3300  | 1.1207          | 0.7170   |
| 1.1483        | 0.8447 | 3400  | 1.0665          | 0.7245   |
| 1.453         | 0.8696 | 3500  | 1.0640          | 0.7267   |
| 1.4457        | 0.8944 | 3600  | 1.0565          | 0.7321   |
| 1.1636        | 0.9193 | 3700  | 1.0576          | 0.7255   |
| 1.157         | 0.9441 | 3800  | 1.0648          | 0.7261   |
| 1.1923        | 0.9689 | 3900  | 1.0473          | 0.7271   |
| 1.2325        | 0.9938 | 4000  | 1.0501          | 0.7298   |
| 1.1503        | 1.0186 | 4100  | 1.0566          | 0.7243   |
| 1.0633        | 1.0435 | 4200  | 1.0005          | 0.7444   |
| 1.2061        | 1.0683 | 4300  | 1.0196          | 0.7377   |
| 1.0315        | 1.0932 | 4400  | 1.0139          | 0.7392   |
| 1.038         | 1.1180 | 4500  | 1.0299          | 0.7318   |
| 0.7728        | 1.1429 | 4600  | 1.0522          | 0.7257   |
| 0.9302        | 1.1677 | 4700  | 1.0219          | 0.7362   |
| 1.1084        | 1.1925 | 4800  | 0.9940          | 0.7349   |
| 1.0345        | 1.2174 | 4900  | 0.9775          | 0.7446   |
| 1.0541        | 1.2422 | 5000  | 1.0076          | 0.7366   |
| 0.9345        | 1.2671 | 5100  | 1.0075          | 0.7398   |
| 0.9149        | 1.2919 | 5200  | 1.0558          | 0.7261   |
| 1.2583        | 1.3168 | 5300  | 0.9703          | 0.7476   |
| 1.0745        | 1.3416 | 5400  | 0.9902          | 0.7425   |
| 0.8319        | 1.3665 | 5500  | 0.9442          | 0.7553   |
| 1.1286        | 1.3913 | 5600  | 0.9620          | 0.7532   |
| 0.8228        | 1.4161 | 5700  | 0.9329          | 0.7555   |
| 1.3209        | 1.4410 | 5800  | 0.9402          | 0.7543   |
| 0.7629        | 1.4658 | 5900  | 0.9497          | 0.7547   |
| 0.9906        | 1.4907 | 6000  | 0.9362          | 0.7589   |
| 0.9966        | 1.5155 | 6100  | 0.9322          | 0.7595   |
| 0.8868        | 1.5404 | 6200  | 0.9613          | 0.7506   |
| 0.956         | 1.5652 | 6300  | 0.9370          | 0.7568   |
| 1.1833        | 1.5901 | 6400  | 0.9277          | 0.7597   |
| 0.9747        | 1.6149 | 6500  | 0.8777          | 0.7696   |
| 1.0119        | 1.6398 | 6600  | 0.8980          | 0.7653   |
| 0.9764        | 1.6646 | 6700  | 0.9071          | 0.7641   |
| 1.0528        | 1.6894 | 6800  | 0.8941          | 0.7694   |
| 0.942         | 1.7143 | 6900  | 0.8718          | 0.7737   |
| 1.0387        | 1.7391 | 7000  | 0.8615          | 0.7787   |
| 0.9054        | 1.7640 | 7100  | 0.8689          | 0.7735   |
| 1.0327        | 1.7888 | 7200  | 0.8953          | 0.7692   |
| 0.8425        | 1.8137 | 7300  | 0.8533          | 0.7761   |
| 0.9388        | 1.8385 | 7400  | 0.8772          | 0.7687   |
| 1.1037        | 1.8634 | 7500  | 0.8634          | 0.7731   |
| 0.9659        | 1.8882 | 7600  | 0.8502          | 0.7766   |
| 1.0133        | 1.9130 | 7700  | 0.8479          | 0.7766   |
| 0.8395        | 1.9379 | 7800  | 0.8052          | 0.7889   |
| 0.8803        | 1.9627 | 7900  | 0.8379          | 0.7775   |
| 0.7866        | 1.9876 | 8000  | 0.8283          | 0.7835   |
| 0.5067        | 2.0124 | 8100  | 0.8207          | 0.7835   |
| 0.7083        | 2.0373 | 8200  | 0.8320          | 0.7803   |
| 0.6581        | 2.0621 | 8300  | 0.8162          | 0.7869   |
| 0.7376        | 2.0870 | 8400  | 0.8222          | 0.7871   |
| 0.6492        | 2.1118 | 8500  | 0.8153          | 0.7868   |
| 0.6356        | 2.1366 | 8600  | 0.7930          | 0.7929   |
| 0.7626        | 2.1615 | 8700  | 0.8167          | 0.7874   |
| 0.7389        | 2.1863 | 8800  | 0.8076          | 0.7889   |
| 0.503         | 2.2112 | 8900  | 0.8312          | 0.7869   |
| 0.7901        | 2.2360 | 9000  | 0.8137          | 0.7900   |
| 0.8387        | 2.2609 | 9100  | 0.8207          | 0.7832   |
| 0.7048        | 2.2857 | 9200  | 0.8105          | 0.7898   |
| 0.6412        | 2.3106 | 9300  | 0.7829          | 0.7950   |
| 0.6864        | 2.3354 | 9400  | 0.7851          | 0.7941   |
| 0.7411        | 2.3602 | 9500  | 0.7642          | 0.8031   |
| 0.6221        | 2.3851 | 9600  | 0.7603          | 0.8030   |
| 0.7769        | 2.4099 | 9700  | 0.7846          | 0.7975   |
| 0.7939        | 2.4348 | 9800  | 0.7914          | 0.7933   |
| 0.5641        | 2.4596 | 9900  | 0.7700          | 0.7992   |
| 0.8009        | 2.4845 | 10000 | 0.7699          | 0.8015   |
| 0.6111        | 2.5093 | 10100 | 0.7603          | 0.8036   |
| 0.925         | 2.5342 | 10200 | 0.7727          | 0.8003   |
| 0.6206        | 2.5590 | 10300 | 0.7765          | 0.7984   |
| 0.5977        | 2.5839 | 10400 | 0.7793          | 0.7960   |
| 0.8146        | 2.6087 | 10500 | 0.7799          | 0.7978   |
| 0.7869        | 2.6335 | 10600 | 0.7396          | 0.8087   |
| 0.8966        | 2.6584 | 10700 | 0.7386          | 0.8071   |
| 0.6654        | 2.6832 | 10800 | 0.7305          | 0.8103   |
| 0.737         | 2.7081 | 10900 | 0.7317          | 0.8083   |
| 0.9283        | 2.7329 | 11000 | 0.7409          | 0.8072   |
| 0.7491        | 2.7578 | 11100 | 0.7088          | 0.8153   |
| 0.6807        | 2.7826 | 11200 | 0.7154          | 0.8123   |
| 0.4485        | 2.8075 | 11300 | 0.6985          | 0.8180   |
| 0.6694        | 2.8323 | 11400 | 0.7124          | 0.8147   |
| 0.6661        | 2.8571 | 11500 | 0.7075          | 0.8153   |
| 0.7971        | 2.8820 | 11600 | 0.7375          | 0.8078   |
| 0.9771        | 2.9068 | 11700 | 0.7133          | 0.8133   |
| 0.5238        | 2.9317 | 11800 | 0.7077          | 0.8157   |
| 0.5636        | 2.9565 | 11900 | 0.7419          | 0.8030   |
| 0.8962        | 2.9814 | 12000 | 0.7021          | 0.8175   |
| 0.4561        | 3.0062 | 12100 | 0.7031          | 0.8162   |
| 0.4906        | 3.0311 | 12200 | 0.7104          | 0.8171   |
| 0.5422        | 3.0559 | 12300 | 0.7035          | 0.8154   |
| 0.5541        | 3.0807 | 12400 | 0.6905          | 0.8232   |
| 0.5009        | 3.1056 | 12500 | 0.6994          | 0.8173   |
| 0.4567        | 3.1304 | 12600 | 0.6911          | 0.8203   |
| 0.4431        | 3.1553 | 12700 | 0.6933          | 0.8192   |
| 0.5915        | 3.1801 | 12800 | 0.6838          | 0.8221   |
| 0.5551        | 3.2050 | 12900 | 0.6886          | 0.8199   |
| 0.4528        | 3.2298 | 13000 | 0.6883          | 0.8212   |
| 0.5563        | 3.2547 | 13100 | 0.6867          | 0.8192   |
| 0.4836        | 3.2795 | 13200 | 0.6771          | 0.8253   |
| 0.4535        | 3.3043 | 13300 | 0.6713          | 0.8249   |
| 0.468         | 3.3292 | 13400 | 0.6616          | 0.8270   |
| 0.4691        | 3.3540 | 13500 | 0.6707          | 0.8261   |
| 0.4784        | 3.3789 | 13600 | 0.6733          | 0.8241   |
| 0.5187        | 3.4037 | 13700 | 0.6658          | 0.8251   |
| 0.5105        | 3.4286 | 13800 | 0.6631          | 0.8275   |
| 0.3935        | 3.4534 | 13900 | 0.6656          | 0.8283   |
| 0.463         | 3.4783 | 14000 | 0.6554          | 0.8301   |
| 0.3259        | 3.5031 | 14100 | 0.6640          | 0.8292   |
| 0.7286        | 3.5280 | 14200 | 0.6500          | 0.8308   |
| 0.4422        | 3.5528 | 14300 | 0.6540          | 0.8313   |
| 0.4374        | 3.5776 | 14400 | 0.6497          | 0.8317   |
| 0.7962        | 3.6025 | 14500 | 0.6416          | 0.8340   |
| 0.6297        | 3.6273 | 14600 | 0.6393          | 0.8339   |
| 0.4933        | 3.6522 | 14700 | 0.6379          | 0.8336   |
| 0.5548        | 3.6770 | 14800 | 0.6300          | 0.8356   |
| 0.564         | 3.7019 | 14900 | 0.6284          | 0.8352   |
| 0.2638        | 3.7267 | 15000 | 0.6299          | 0.8338   |
| 0.6129        | 3.7516 | 15100 | 0.6253          | 0.8374   |
| 0.51          | 3.7764 | 15200 | 0.6205          | 0.8390   |
| 0.4612        | 3.8012 | 15300 | 0.6165          | 0.8390   |
| 0.5304        | 3.8261 | 15400 | 0.6112          | 0.8412   |
| 0.4738        | 3.8509 | 15500 | 0.6149          | 0.8388   |
| 0.3845        | 3.8758 | 15600 | 0.6141          | 0.8391   |
| 0.4533        | 3.9006 | 15700 | 0.6139          | 0.8399   |
| 0.3539        | 3.9255 | 15800 | 0.6131          | 0.8402   |
| 0.6485        | 3.9503 | 15900 | 0.6118          | 0.8397   |
| 0.331         | 3.9752 | 16000 | 0.6108          | 0.8397   |
| 0.3582        | 4.0    | 16100 | 0.6105          | 0.8400   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1

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