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# DeepFake-EN-B6

This model is a fine-tuned version of [google/efficientnet-b6](https://huggingface.co/google/efficientnet-b6) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0036
- Accuracy: 0.9989

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0076        | 0.9998 | 2187 | 0.0088          | 0.9970   |
| 0.002         | 2.0    | 4375 | 0.0173          | 0.9931   |
| 0.0011        | 2.4997 | 5468 | 0.0036          | 0.9989   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1

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