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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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2731
- Accuracy: 0.9256

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6673        | 0.3003 | 100  | 0.6440          | 0.8725   |
| 0.5605        | 0.6006 | 200  | 0.5161          | 0.8842   |
| 0.4987        | 0.9009 | 300  | 0.4620          | 0.8831   |
| 0.4189        | 1.2012 | 400  | 0.4331          | 0.8799   |
| 0.5467        | 1.5015 | 500  | 0.4510          | 0.8767   |
| 0.3063        | 1.8018 | 600  | 0.4201          | 0.8916   |
| 0.2835        | 2.1021 | 700  | 0.3326          | 0.9182   |
| 0.2514        | 2.4024 | 800  | 0.4134          | 0.8874   |
| 0.2146        | 2.7027 | 900  | 0.3187          | 0.9129   |
| 0.2022        | 3.0030 | 1000 | 0.2949          | 0.9235   |
| 0.2299        | 3.3033 | 1100 | 0.2753          | 0.9309   |
| 0.2333        | 3.6036 | 1200 | 0.2699          | 0.9288   |
| 0.1469        | 3.9039 | 1300 | 0.2731          | 0.9256   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0

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