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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: 1.0801
- Accuracy: 0.675

## 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: 6e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 23   | 1.0917          | 0.625    |
| No log        | 2.0   | 46   | 1.1605          | 0.6125   |
| No log        | 3.0   | 69   | 1.0543          | 0.6375   |
| No log        | 4.0   | 92   | 1.1663          | 0.6      |
| No log        | 5.0   | 115  | 1.2546          | 0.5875   |
| No log        | 6.0   | 138  | 1.0580          | 0.6      |
| No log        | 7.0   | 161  | 1.1193          | 0.6125   |
| No log        | 8.0   | 184  | 1.2297          | 0.525    |
| No log        | 9.0   | 207  | 1.2295          | 0.55     |
| No log        | 10.0  | 230  | 1.0842          | 0.6125   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1

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