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# vit-superhero-villain

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2902
- Accuracy: 0.7363

## 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: 64
- eval_batch_size: 8
- 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 26   | 1.4140          | 0.735    |
| 1.2713        | 2.0   | 52   | 1.3908          | 0.735    |
| 1.2713        | 3.0   | 78   | 1.3709          | 0.735    |
| 1.2028        | 4.0   | 104  | 1.3544          | 0.74     |
| 1.2028        | 5.0   | 130  | 1.3359          | 0.74     |
| 1.1776        | 6.0   | 156  | 1.3219          | 0.74     |
| 1.1776        | 7.0   | 182  | 1.3078          | 0.74     |
| 1.1515        | 8.0   | 208  | 1.2952          | 0.74     |
| 1.1515        | 9.0   | 234  | 1.2841          | 0.74     |
| 1.1519        | 10.0  | 260  | 1.2733          | 0.745    |
| 1.1519        | 11.0  | 286  | 1.2637          | 0.745    |
| 1.107         | 12.0  | 312  | 1.2557          | 0.745    |
| 1.107         | 13.0  | 338  | 1.2495          | 0.745    |
| 1.0611        | 14.0  | 364  | 1.2441          | 0.745    |
| 1.0611        | 15.0  | 390  | 1.2388          | 0.745    |
| 1.0748        | 16.0  | 416  | 1.2347          | 0.745    |
| 1.0748        | 17.0  | 442  | 1.2317          | 0.745    |
| 1.0563        | 18.0  | 468  | 1.2294          | 0.745    |
| 1.0563        | 19.0  | 494  | 1.2280          | 0.745    |
| 1.062         | 20.0  | 520  | 1.2277          | 0.745    |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.5.1+cu121
- Datasets 3.5.0
- Tokenizers 0.21.1

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