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# 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 indian_food_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2249
- Accuracy: 0.9416

## 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: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3083        | 0.6   | 100  | 0.3674          | 0.9139   |
| 0.3447        | 1.2   | 200  | 0.2912          | 0.9277   |
| 0.3753        | 1.8   | 300  | 0.2817          | 0.9245   |
| 0.1742        | 2.4   | 400  | 0.2506          | 0.9320   |
| 0.1844        | 2.99  | 500  | 0.2511          | 0.9416   |
| 0.1797        | 3.59  | 600  | 0.2249          | 0.9416   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

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