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# results

This model is a fine-tuned version of [google/vit-base-patch32-224-in21k](https://huggingface.co/google/vit-base-patch32-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4692
- Accuracy: 0.4562

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7426        | 1.0   | 40   | 1.4692          | 0.4562   |
| 0.4647        | 2.0   | 80   | 1.5033          | 0.4313   |
| 0.2527        | 3.0   | 120  | 1.5517          | 0.4813   |
| 0.1551        | 4.0   | 160  | 1.6071          | 0.4688   |
| 0.113         | 5.0   | 200  | 1.6474          | 0.475    |
| 0.0914        | 6.0   | 240  | 1.6752          | 0.45     |
| 0.0774        | 7.0   | 280  | 1.7003          | 0.45     |
| 0.0698        | 8.0   | 320  | 1.7336          | 0.4437   |
| 0.063         | 9.0   | 360  | 1.7595          | 0.45     |
| 0.0583        | 10.0  | 400  | 1.7778          | 0.4437   |
| 0.0551        | 11.0  | 440  | 1.7938          | 0.4375   |
| 0.0531        | 12.0  | 480  | 1.8082          | 0.4375   |
| 0.0509        | 13.0  | 520  | 1.8176          | 0.4437   |
| 0.0499        | 14.0  | 560  | 1.8230          | 0.4375   |
| 0.0494        | 15.0  | 600  | 1.8249          | 0.4375   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1
- Datasets 2.21.0
- Tokenizers 0.19.1

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7