
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# finetuned-indian-food

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 food_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2373
- Accuracy: 0.9394
- Precision: 0.9406
- Recall: 0.9410
- F1: 0.9401

## 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.14          | 0.3   | 100  | 0.9144          | 0.8597   | 0.8756    | 0.8451 | 0.8349 |
| 0.8065        | 0.6   | 200  | 0.6736          | 0.8480   | 0.8735    | 0.8493 | 0.8473 |
| 0.5949        | 0.9   | 300  | 0.4965          | 0.8895   | 0.9046    | 0.8946 | 0.8941 |
| 0.4925        | 1.2   | 400  | 0.4049          | 0.9033   | 0.9084    | 0.9069 | 0.9051 |
| 0.3748        | 1.5   | 500  | 0.3852          | 0.9075   | 0.9129    | 0.9054 | 0.9065 |
| 0.3121        | 1.8   | 600  | 0.3422          | 0.9150   | 0.9183    | 0.9158 | 0.9148 |
| 0.3826        | 2.1   | 700  | 0.3406          | 0.9065   | 0.9137    | 0.9054 | 0.9076 |
| 0.2485        | 2.4   | 800  | 0.2915          | 0.9299   | 0.9298    | 0.9299 | 0.9282 |
| 0.2177        | 2.7   | 900  | 0.2520          | 0.9330   | 0.9333    | 0.9337 | 0.9327 |
| 0.1546        | 3.0   | 1000 | 0.2498          | 0.9384   | 0.9448    | 0.9385 | 0.9398 |
| 0.2157        | 3.3   | 1100 | 0.2658          | 0.9320   | 0.9329    | 0.9330 | 0.9318 |
| 0.0799        | 3.6   | 1200 | 0.2469          | 0.9384   | 0.9402    | 0.9394 | 0.9391 |
| 0.2242        | 3.9   | 1300 | 0.2373          | 0.9394   | 0.9406    | 0.9410 | 0.9401 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

burger butter_naan kaathi_rolls kadai_paneer kulfi masala_dosa momos paani_puri pakode pav_bhaji pizza samosa chai chapati chole_bhature dal_makhani dhokla fried_rice idli jalebi