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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: 1.2386
- Accuracy: 0.5625

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0874        | 1.0   | 10   | 2.0621          | 0.2313   |
| 2.036         | 2.0   | 20   | 2.0392          | 0.2375   |
| 1.9297        | 3.0   | 30   | 1.9592          | 0.3      |
| 1.7723        | 4.0   | 40   | 1.7877          | 0.3937   |
| 1.6184        | 5.0   | 50   | 1.6475          | 0.45     |
| 1.5407        | 6.0   | 60   | 1.5514          | 0.4875   |
| 1.4197        | 7.0   | 70   | 1.4967          | 0.4938   |
| 1.3092        | 8.0   | 80   | 1.4332          | 0.4813   |
| 1.1251        | 9.0   | 90   | 1.4457          | 0.4688   |
| 1.2081        | 10.0  | 100  | 1.3603          | 0.4938   |
| 0.9803        | 11.0  | 110  | 1.3501          | 0.5188   |
| 1.0105        | 12.0  | 120  | 1.3212          | 0.55     |
| 0.9264        | 13.0  | 130  | 1.2895          | 0.575    |
| 0.9229        | 14.0  | 140  | 1.2882          | 0.5188   |
| 0.9397        | 15.0  | 150  | 1.4027          | 0.475    |
| 0.8322        | 16.0  | 160  | 1.2824          | 0.5312   |
| 0.8185        | 17.0  | 170  | 1.3025          | 0.5      |
| 0.7592        | 18.0  | 180  | 1.3629          | 0.475    |
| 0.7416        | 19.0  | 190  | 1.3221          | 0.5437   |
| 0.6323        | 20.0  | 200  | 1.2714          | 0.5563   |
| 0.6453        | 21.0  | 210  | 1.3015          | 0.4938   |
| 0.6049        | 22.0  | 220  | 1.3065          | 0.5375   |
| 0.5919        | 23.0  | 230  | 1.2579          | 0.5375   |
| 0.5354        | 24.0  | 240  | 1.2428          | 0.55     |
| 0.6379        | 25.0  | 250  | 1.2884          | 0.5375   |
| 0.5681        | 26.0  | 260  | 1.2201          | 0.5938   |
| 0.4275        | 27.0  | 270  | 1.3199          | 0.4875   |
| 0.4791        | 28.0  | 280  | 1.3027          | 0.5312   |
| 0.4693        | 29.0  | 290  | 1.3737          | 0.4813   |
| 0.5528        | 30.0  | 300  | 1.3342          | 0.4688   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1

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