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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: 0.7094
- Accuracy: 0.845

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 50   | 1.3475          | 0.56     |
| No log        | 2.0   | 100  | 1.1865          | 0.6325   |
| No log        | 3.0   | 150  | 1.0930          | 0.6675   |
| No log        | 4.0   | 200  | 0.9387          | 0.7612   |
| No log        | 5.0   | 250  | 0.8322          | 0.7963   |
| No log        | 6.0   | 300  | 0.7693          | 0.8337   |
| No log        | 7.0   | 350  | 0.7215          | 0.8462   |
| No log        | 8.0   | 400  | 0.7103          | 0.85     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2

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