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# train_dir

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.
This Model fine tunes the google Vit transformer model with the fake and real face images . This model can cen be utilzied 
for vlaidating a given face image is a Fake or real face image
It achieves the following results on the evaluation set:
- Loss: 0.0852
- Accuracy: 0.975

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.325         | 1.0   | 438  | 0.2307          | 0.9083   |
| 0.198         | 2.0   | 876  | 0.2022          | 0.925    |
| 0.1401        | 3.0   | 1314 | 0.1086          | 0.9657   |
| 0.1044        | 4.0   | 1752 | 0.0859          | 0.975    |
| 0.0098        | 5.0   | 2190 | 0.0852          | 0.975    |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1

fake real