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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: 1.2727
- Accuracy: 0.5312

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0804        | 1.0   | 10   | 2.0714          | 0.1625   |
| 2.0428        | 2.0   | 20   | 2.0324          | 0.2313   |
| 1.9463        | 3.0   | 30   | 1.8978          | 0.3438   |
| 1.7768        | 4.0   | 40   | 1.7234          | 0.375    |
| 1.6163        | 5.0   | 50   | 1.6029          | 0.4188   |
| 1.509         | 6.0   | 60   | 1.5122          | 0.5      |
| 1.4118        | 7.0   | 70   | 1.4839          | 0.4375   |
| 1.3381        | 8.0   | 80   | 1.4268          | 0.475    |
| 1.2653        | 9.0   | 90   | 1.4095          | 0.4813   |
| 1.1979        | 10.0  | 100  | 1.3504          | 0.5375   |
| 1.1219        | 11.0  | 110  | 1.3293          | 0.4875   |
| 1.0858        | 12.0  | 120  | 1.3023          | 0.4875   |
| 1.0214        | 13.0  | 130  | 1.3063          | 0.5188   |
| 1.0085        | 14.0  | 140  | 1.3306          | 0.5312   |
| 0.9615        | 15.0  | 150  | 1.2838          | 0.5      |
| 0.9277        | 16.0  | 160  | 1.3073          | 0.5125   |
| 0.898         | 17.0  | 170  | 1.2606          | 0.5437   |
| 0.8747        | 18.0  | 180  | 1.3116          | 0.5437   |
| 0.8657        | 19.0  | 190  | 1.3171          | 0.5375   |
| 0.8462        | 20.0  | 200  | 1.2619          | 0.525    |


### Framework versions

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

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