| ---
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| license: apache-2.0
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| base_model: google/vit-base-patch16-384
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| tags:
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| - generated_from_trainer
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| metrics:
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| - accuracy
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| model-index:
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| - name: DeepFake-image-detection-ViT-384
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| results: []
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| ---
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|
|
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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| should probably proofread and complete it, then remove this comment. -->
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|
|
| # DeepFake-image-detection-ViT-384
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| This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset.
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| It achieves the following results on the evaluation set:
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| - Loss: 0.0272
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| - Accuracy: 0.9911
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|
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| ## Model description
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| More information needed
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|
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| ## Intended uses & limitations
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| More information needed
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|
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| ## Training and evaluation data
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| More information needed
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|
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| ## Training procedure
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|
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| ### Training hyperparameters
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| The following hyperparameters were used during training:
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| - learning_rate: 3e-05
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| - train_batch_size: 32
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| - eval_batch_size: 32
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| - seed: 42
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| - gradient_accumulation_steps: 8
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| - total_train_batch_size: 256
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| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| - lr_scheduler_type: cosine
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| - lr_scheduler_warmup_ratio: 0.1
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| - num_epochs: 2.5
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| - mixed_precision_training: Native AMP
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|
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| ### Training results
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| | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| |:-------------:|:------:|:----:|:---------------:|:--------:|
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| | 0.0037 | 0.9984 | 546 | 0.0272 | 0.9911 |
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| | 0.0006 | 1.9986 | 1093 | 0.1121 | 0.9644 |
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| | 0.0002 | 2.496 | 1365 | 0.1357 | 0.9582 |
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| ### Framework versions
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| - Transformers 4.41.2
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| - Pytorch 2.1.2
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| - Datasets 2.19.2
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| - Tokenizers 0.19.1
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