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# MobileNet-V2-food

This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the ItsNotRohit/Food121-224 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6890
- Accuracy: 0.5793
- Recall: 0.5793
- Precision: 0.6006
- F1: 0.5769

## 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: 128
- seed: 20329
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 20000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Recall | Precision | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 2.9653        | 0.33  | 2000  | 2.7802          | 0.3438   | 0.3438 | 0.3932    | 0.3105 |
| 2.3854        | 0.66  | 4000  | 2.3105          | 0.4440   | 0.4440 | 0.4979    | 0.4336 |
| 2.1576        | 0.99  | 6000  | 2.0508          | 0.4958   | 0.4958 | 0.5263    | 0.4837 |
| 1.9767        | 1.32  | 8000  | 1.9860          | 0.5086   | 0.5086 | 0.5504    | 0.4956 |
| 1.9215        | 1.65  | 10000 | 1.8312          | 0.5462   | 0.5462 | 0.5815    | 0.5390 |
| 1.782         | 1.98  | 12000 | 1.8554          | 0.5441   | 0.5441 | 0.5864    | 0.5431 |
| 1.7755        | 2.31  | 14000 | 1.9241          | 0.5308   | 0.5308 | 0.5841    | 0.5272 |
| 1.7006        | 2.64  | 16000 | 1.8625          | 0.5451   | 0.5451 | 0.6004    | 0.5466 |
| 1.7289        | 2.98  | 18000 | 1.8560          | 0.5432   | 0.5432 | 0.5940    | 0.5395 |
| 1.7296        | 3.31  | 20000 | 1.6890          | 0.5793   | 0.5793 | 0.6006    | 0.5769 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

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