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# image_classification

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1877
- Accuracy: 0.625

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 40   | 1.8317          | 0.2938   |
| No log        | 2.0   | 80   | 1.5647          | 0.4437   |
| No log        | 3.0   | 120  | 1.4497          | 0.4938   |
| No log        | 4.0   | 160  | 1.3529          | 0.5188   |
| No log        | 5.0   | 200  | 1.2883          | 0.5125   |
| No log        | 6.0   | 240  | 1.2861          | 0.5125   |
| No log        | 7.0   | 280  | 1.2655          | 0.55     |
| No log        | 8.0   | 320  | 1.2890          | 0.5125   |
| No log        | 9.0   | 360  | 1.1955          | 0.575    |
| No log        | 10.0  | 400  | 1.2180          | 0.5687   |
| No log        | 11.0  | 440  | 1.2835          | 0.55     |
| No log        | 12.0  | 480  | 1.2838          | 0.5188   |
| 1.0368        | 13.0  | 520  | 1.2168          | 0.5875   |
| 1.0368        | 14.0  | 560  | 1.1713          | 0.6312   |
| 1.0368        | 15.0  | 600  | 1.2222          | 0.5875   |
| 1.0368        | 16.0  | 640  | 1.3160          | 0.5563   |
| 1.0368        | 17.0  | 680  | 1.2512          | 0.6125   |
| 1.0368        | 18.0  | 720  | 1.3575          | 0.5563   |
| 1.0368        | 19.0  | 760  | 1.3514          | 0.5375   |
| 1.0368        | 20.0  | 800  | 1.3472          | 0.5625   |
| 1.0368        | 21.0  | 840  | 1.3449          | 0.5375   |
| 1.0368        | 22.0  | 880  | 1.3783          | 0.5375   |
| 1.0368        | 23.0  | 920  | 1.3240          | 0.575    |
| 1.0368        | 24.0  | 960  | 1.3391          | 0.5687   |
| 0.2885        | 25.0  | 1000 | 1.3723          | 0.55     |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3

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