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# finetuned-indian-food-9

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_9 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3239
- Accuracy: 0.9227

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.3678        | 0.2874 | 100  | 1.2110          | 0.8291   |
| 0.8714        | 0.5747 | 200  | 0.8336          | 0.8494   |
| 0.8788        | 0.8621 | 300  | 0.6678          | 0.8474   |
| 0.5413        | 1.1494 | 400  | 0.5275          | 0.8850   |
| 0.4618        | 1.4368 | 500  | 0.5324          | 0.8688   |
| 0.4924        | 1.7241 | 600  | 0.5178          | 0.8698   |
| 0.3667        | 2.0115 | 700  | 0.4564          | 0.8942   |
| 0.2604        | 2.2989 | 800  | 0.4188          | 0.8973   |
| 0.2148        | 2.5862 | 900  | 0.4108          | 0.8993   |
| 0.2383        | 2.8736 | 1000 | 0.3312          | 0.9145   |
| 0.1441        | 3.1609 | 1100 | 0.3467          | 0.9156   |
| 0.186         | 3.4483 | 1200 | 0.3284          | 0.9237   |
| 0.19          | 3.7356 | 1300 | 0.3239          | 0.9227   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0

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