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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: 1.2152
- Accuracy: 0.5687

## 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 40   | 1.3484          | 0.5437   |
| No log        | 2.0   | 80   | 1.3268          | 0.4875   |
| No log        | 3.0   | 120  | 1.2463          | 0.5437   |
| No log        | 4.0   | 160  | 1.2361          | 0.5563   |
| No log        | 5.0   | 200  | 1.2089          | 0.5813   |
| No log        | 6.0   | 240  | 1.2544          | 0.525    |
| No log        | 7.0   | 280  | 1.1947          | 0.5563   |
| No log        | 8.0   | 320  | 1.2502          | 0.5188   |
| No log        | 9.0   | 360  | 1.3415          | 0.4938   |
| No log        | 10.0  | 400  | 1.1336          | 0.6      |
| No log        | 11.0  | 440  | 1.2716          | 0.5437   |
| No log        | 12.0  | 480  | 1.4631          | 0.5      |
| 0.6882        | 13.0  | 520  | 1.3970          | 0.5563   |
| 0.6882        | 14.0  | 560  | 1.2654          | 0.5188   |
| 0.6882        | 15.0  | 600  | 1.2498          | 0.575    |
| 0.6882        | 16.0  | 640  | 1.2655          | 0.5938   |
| 0.6882        | 17.0  | 680  | 1.3577          | 0.55     |
| 0.6882        | 18.0  | 720  | 1.2711          | 0.5813   |
| 0.6882        | 19.0  | 760  | 1.3127          | 0.5687   |
| 0.6882        | 20.0  | 800  | 1.2478          | 0.575    |


### Framework versions

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

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