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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: 0.2335
- Accuracy: 0.9405

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1519        | 0.3   | 100  | 0.9412          | 0.8502   |
| 0.8102        | 0.6   | 200  | 0.5750          | 0.8767   |
| 0.6965        | 0.9   | 300  | 0.5096          | 0.8799   |
| 0.3846        | 1.2   | 400  | 0.4313          | 0.8874   |
| 0.4424        | 1.5   | 500  | 0.3873          | 0.9012   |
| 0.3842        | 1.8   | 600  | 0.4032          | 0.8916   |
| 0.3387        | 2.1   | 700  | 0.3029          | 0.9160   |
| 0.2245        | 2.4   | 800  | 0.2894          | 0.9288   |
| 0.2865        | 2.7   | 900  | 0.2663          | 0.9299   |
| 0.2523        | 3.0   | 1000 | 0.2670          | 0.9277   |
| 0.1973        | 3.3   | 1100 | 0.2375          | 0.9373   |
| 0.0956        | 3.6   | 1200 | 0.2457          | 0.9373   |
| 0.1013        | 3.9   | 1300 | 0.2335          | 0.9405   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.0.1+cu117
- 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