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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: 1.1140
- Accuracy: 0.6125

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9952        | 1.0   | 10   | 2.0130          | 0.3063   |
| 1.9609        | 2.0   | 20   | 1.9619          | 0.3563   |
| 1.8939        | 3.0   | 30   | 1.8425          | 0.4188   |
| 1.7588        | 4.0   | 40   | 1.6837          | 0.45     |
| 1.6045        | 5.0   | 50   | 1.5389          | 0.4688   |
| 1.4959        | 6.0   | 60   | 1.4618          | 0.5062   |
| 1.3876        | 7.0   | 70   | 1.3693          | 0.5375   |
| 1.295         | 8.0   | 80   | 1.3286          | 0.575    |
| 1.2328        | 9.0   | 90   | 1.3112          | 0.5563   |
| 1.1447        | 10.0  | 100  | 1.2627          | 0.5813   |
| 1.0791        | 11.0  | 110  | 1.2462          | 0.5813   |
| 1.0378        | 12.0  | 120  | 1.2410          | 0.6      |
| 1.0013        | 13.0  | 130  | 1.2353          | 0.5687   |
| 0.9512        | 14.0  | 140  | 1.2324          | 0.5625   |
| 0.8505        | 15.0  | 150  | 1.2216          | 0.575    |
| 0.8193        | 16.0  | 160  | 1.2061          | 0.6      |
| 0.7379        | 17.0  | 170  | 1.1829          | 0.5563   |
| 0.7133        | 18.0  | 180  | 1.2131          | 0.5625   |
| 0.6582        | 19.0  | 190  | 1.1882          | 0.5625   |
| 0.6663        | 20.0  | 200  | 1.0910          | 0.6188   |
| 0.589         | 21.0  | 210  | 1.1769          | 0.5687   |
| 0.5865        | 22.0  | 220  | 1.1242          | 0.6375   |
| 0.5336        | 23.0  | 230  | 1.1933          | 0.5375   |
| 0.5168        | 24.0  | 240  | 1.1956          | 0.575    |
| 0.4937        | 25.0  | 250  | 1.1943          | 0.6      |
| 0.487         | 26.0  | 260  | 1.1298          | 0.575    |
| 0.4582        | 27.0  | 270  | 1.1004          | 0.6312   |
| 0.4611        | 28.0  | 280  | 1.1108          | 0.5875   |
| 0.4386        | 29.0  | 290  | 1.2242          | 0.5813   |
| 0.4255        | 30.0  | 300  | 1.1560          | 0.5875   |
| 0.4136        | 31.0  | 310  | 1.2545          | 0.5437   |
| 0.4204        | 32.0  | 320  | 1.1661          | 0.6125   |
| 0.3959        | 33.0  | 330  | 1.1248          | 0.5875   |
| 0.3661        | 34.0  | 340  | 1.1475          | 0.6062   |
| 0.3603        | 35.0  | 350  | 1.1463          | 0.6125   |
| 0.3617        | 36.0  | 360  | 1.2161          | 0.5563   |
| 0.3761        | 37.0  | 370  | 1.2575          | 0.5312   |
| 0.3452        | 38.0  | 380  | 1.1720          | 0.575    |
| 0.3665        | 39.0  | 390  | 1.1165          | 0.6      |
| 0.3471        | 40.0  | 400  | 1.2233          | 0.5375   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0

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