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# Deepfake-image

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0662
- Accuracy: 0.9743

## 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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2672        | 1.0   | 297  | 0.1128          | 0.9577   |
| 0.0958        | 2.0   | 595  | 0.0953          | 0.9634   |
| 0.0816        | 3.0   | 892  | 0.0776          | 0.9694   |
| 0.0712        | 4.0   | 1190 | 0.0746          | 0.9707   |
| 0.0647        | 5.0   | 1487 | 0.0680          | 0.9726   |
| 0.0616        | 6.0   | 1785 | 0.0656          | 0.9735   |
| 0.0565        | 7.0   | 2082 | 0.0676          | 0.9736   |
| 0.0533        | 7.99  | 2376 | 0.0662          | 0.9743   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.19.0
- Tokenizers 0.15.2

fake real