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# my_awesome_food_model_v2

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8053
- Accuracy: 0.8083

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 4.4448        | 0.9932  | 110  | 4.4236          | 0.0914   |
| 3.8312        | 1.9955  | 221  | 3.8007          | 0.4096   |
| 3.1568        | 2.9977  | 332  | 3.1221          | 0.5435   |
| 2.4967        | 4.0     | 443  | 2.4920          | 0.6308   |
| 2.0432        | 4.9932  | 553  | 2.0252          | 0.6825   |
| 1.6512        | 5.9955  | 664  | 1.6771          | 0.7184   |
| 1.388         | 6.9977  | 775  | 1.4464          | 0.7367   |
| 1.1677        | 8.0     | 886  | 1.2782          | 0.7533   |
| 1.0307        | 8.9932  | 996  | 1.1741          | 0.7625   |
| 0.9156        | 9.9955  | 1107 | 1.0900          | 0.7741   |
| 0.8283        | 10.9977 | 1218 | 1.0295          | 0.7771   |
| 0.8078        | 12.0    | 1329 | 0.9949          | 0.7776   |
| 0.7643        | 12.9932 | 1439 | 0.9656          | 0.7817   |
| 0.6578        | 13.9955 | 1550 | 0.9274          | 0.7868   |
| 0.611         | 14.9977 | 1661 | 0.9051          | 0.7921   |
| 0.6016        | 16.0    | 1772 | 0.9009          | 0.7912   |
| 0.5652        | 16.9932 | 1882 | 0.8772          | 0.7963   |
| 0.5492        | 17.9955 | 1993 | 0.8559          | 0.7992   |
| 0.5054        | 18.9977 | 2104 | 0.8734          | 0.7956   |
| 0.5351        | 20.0    | 2215 | 0.8617          | 0.7999   |
| 0.4949        | 20.9932 | 2325 | 0.8487          | 0.8013   |
| 0.4701        | 21.9955 | 2436 | 0.8437          | 0.8013   |
| 0.4576        | 22.9977 | 2547 | 0.8430          | 0.8008   |
| 0.4573        | 24.0    | 2658 | 0.8195          | 0.8071   |
| 0.4399        | 24.9932 | 2768 | 0.8206          | 0.8071   |
| 0.424         | 25.9955 | 2879 | 0.8212          | 0.8068   |
| 0.4031        | 26.9977 | 2990 | 0.8202          | 0.8069   |
| 0.4031        | 28.0    | 3101 | 0.8173          | 0.8080   |
| 0.407         | 28.9932 | 3211 | 0.8051          | 0.8069   |
| 0.4194        | 29.7968 | 3300 | 0.8053          | 0.8083   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- 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