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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: 1.3592
- Accuracy: 0.5

## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 27   | 1.3924          | 0.45     |
| No log        | 2.0   | 54   | 1.3205          | 0.5      |
| No log        | 3.0   | 81   | 1.3110          | 0.5437   |
| No log        | 4.0   | 108  | 1.4055          | 0.475    |
| No log        | 5.0   | 135  | 1.3692          | 0.525    |
| No log        | 6.0   | 162  | 1.3012          | 0.5375   |
| No log        | 7.0   | 189  | 1.3290          | 0.4938   |
| No log        | 8.0   | 216  | 1.3676          | 0.5062   |
| No log        | 9.0   | 243  | 1.2969          | 0.5563   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1

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