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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: 1.4879
- Accuracy: 0.5563

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0789        | 1.0   | 10   | 2.0612          | 0.2      |
| 1.9841        | 2.0   | 20   | 1.9284          | 0.3125   |
| 1.7615        | 3.0   | 30   | 1.6163          | 0.375    |
| 1.4914        | 4.0   | 40   | 1.4871          | 0.4188   |
| 1.3023        | 5.0   | 50   | 1.3431          | 0.4875   |
| 1.1635        | 6.0   | 60   | 1.3240          | 0.4813   |
| 1.0184        | 7.0   | 70   | 1.2126          | 0.5312   |
| 0.8538        | 8.0   | 80   | 1.2680          | 0.525    |
| 0.6981        | 9.0   | 90   | 1.3068          | 0.525    |
| 0.6156        | 10.0  | 100  | 1.4091          | 0.4875   |
| 0.6205        | 11.0  | 110  | 1.3336          | 0.4813   |
| 0.5423        | 12.0  | 120  | 1.4549          | 0.4875   |
| 0.44          | 13.0  | 130  | 1.4772          | 0.5      |
| 0.4233        | 14.0  | 140  | 1.5430          | 0.4625   |
| 0.391         | 15.0  | 150  | 1.3734          | 0.5563   |
| 0.3735        | 16.0  | 160  | 1.5240          | 0.4875   |
| 0.3431        | 17.0  | 170  | 1.5552          | 0.5      |
| 0.3399        | 18.0  | 180  | 1.4532          | 0.5125   |
| 0.3632        | 19.0  | 190  | 1.5218          | 0.5      |
| 0.3171        | 20.0  | 200  | 1.6937          | 0.4813   |
| 0.2326        | 21.0  | 210  | 1.4180          | 0.5625   |
| 0.27          | 22.0  | 220  | 1.6422          | 0.5062   |
| 0.2207        | 23.0  | 230  | 1.7011          | 0.4562   |
| 0.2428        | 24.0  | 240  | 1.8067          | 0.4813   |
| 0.2248        | 25.0  | 250  | 1.6980          | 0.5188   |
| 0.2502        | 26.0  | 260  | 1.6963          | 0.5      |
| 0.1878        | 27.0  | 270  | 1.7788          | 0.5125   |
| 0.2659        | 28.0  | 280  | 1.8155          | 0.4875   |
| 0.1456        | 29.0  | 290  | 1.8315          | 0.475    |
| 0.2087        | 30.0  | 300  | 1.7292          | 0.4938   |
| 0.1779        | 31.0  | 310  | 1.6672          | 0.55     |
| 0.2008        | 32.0  | 320  | 1.7537          | 0.5062   |
| 0.1441        | 33.0  | 330  | 1.7741          | 0.5062   |
| 0.1799        | 34.0  | 340  | 1.8359          | 0.4875   |
| 0.1333        | 35.0  | 350  | 1.9234          | 0.4813   |
| 0.1442        | 36.0  | 360  | 1.9067          | 0.5062   |
| 0.1682        | 37.0  | 370  | 1.8590          | 0.475    |
| 0.1378        | 38.0  | 380  | 1.7157          | 0.4813   |
| 0.1435        | 39.0  | 390  | 1.7980          | 0.5125   |
| 0.1117        | 40.0  | 400  | 1.8570          | 0.5312   |
| 0.1123        | 41.0  | 410  | 1.9124          | 0.4938   |
| 0.0965        | 42.0  | 420  | 1.8322          | 0.5188   |
| 0.1054        | 43.0  | 430  | 1.8154          | 0.5125   |
| 0.1231        | 44.0  | 440  | 1.9575          | 0.5188   |
| 0.098         | 45.0  | 450  | 1.8973          | 0.4938   |
| 0.0769        | 46.0  | 460  | 1.8108          | 0.5563   |
| 0.0862        | 47.0  | 470  | 1.6361          | 0.5563   |
| 0.0904        | 48.0  | 480  | 1.8813          | 0.5188   |
| 0.0871        | 49.0  | 490  | 1.7737          | 0.55     |
| 0.1053        | 50.0  | 500  | 1.8230          | 0.5062   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3

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