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# results

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: 1.3316
- 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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
- num_epochs: 13

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0192        | 1.0   | 40   | 1.9801          | 0.2687   |
| 1.7656        | 2.0   | 80   | 1.8060          | 0.4375   |
| 1.5519        | 3.0   | 120  | 1.6564          | 0.4625   |
| 1.3524        | 4.0   | 160  | 1.5762          | 0.475    |
| 1.1584        | 5.0   | 200  | 1.5078          | 0.5062   |
| 0.9827        | 6.0   | 240  | 1.4490          | 0.525    |
| 0.8292        | 7.0   | 280  | 1.4027          | 0.525    |
| 0.6822        | 8.0   | 320  | 1.3633          | 0.5312   |
| 0.5564        | 9.0   | 360  | 1.3588          | 0.5062   |
| 0.4856        | 10.0  | 400  | 1.3466          | 0.525    |
| 0.4572        | 11.0  | 440  | 1.3391          | 0.5437   |
| 0.4064        | 12.0  | 480  | 1.3316          | 0.5563   |
| 0.3951        | 13.0  | 520  | 1.3293          | 0.5563   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7