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# imageclassification

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: 1.3551
- Accuracy: 0.55

## 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   | 1.8154          | 0.3375   |
| No log        | 2.0   | 80   | 1.5714          | 0.35     |
| No log        | 3.0   | 120  | 1.4703          | 0.4688   |
| No log        | 4.0   | 160  | 1.3945          | 0.4688   |
| No log        | 5.0   | 200  | 1.3476          | 0.5312   |
| No log        | 6.0   | 240  | 1.2977          | 0.5062   |
| No log        | 7.0   | 280  | 1.3201          | 0.525    |
| No log        | 8.0   | 320  | 1.3392          | 0.4875   |
| No log        | 9.0   | 360  | 1.2970          | 0.5188   |
| No log        | 10.0  | 400  | 1.3250          | 0.4938   |
| No log        | 11.0  | 440  | 1.3276          | 0.525    |
| No log        | 12.0  | 480  | 1.3386          | 0.5125   |
| 1.051         | 13.0  | 520  | 1.2965          | 0.5375   |
| 1.051         | 14.0  | 560  | 1.3555          | 0.5375   |
| 1.051         | 15.0  | 600  | 1.2991          | 0.5312   |
| 1.051         | 16.0  | 640  | 1.3825          | 0.4875   |
| 1.051         | 17.0  | 680  | 1.3032          | 0.5563   |
| 1.051         | 18.0  | 720  | 1.4365          | 0.5      |
| 1.051         | 19.0  | 760  | 1.3717          | 0.5125   |
| 1.051         | 20.0  | 800  | 1.3675          | 0.525    |


### Framework versions

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

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