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--- |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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base_model: |
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- google/vit-base-patch16-224-in21k |
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pipeline_tag: image-classification |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- Python |
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- Deepfake |
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--- |
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# Deepfake Image Detection Using Fine-Tuned Vision Transformer (ViT) |
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This project focuses on detecting **deepfake images** using a fine-tuned version of the pre-trained model `google/vit-base-patch16-224-in21k`. The approach leverages the power of Vision Transformers (ViT) to classify images as real or fake. |
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## **Model Overview** |
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- **Base Model**: [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) |
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- **Dataset**: [DFDC](https://ai.meta.com/datasets/dfdc). |
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- **Classes**: Deepfake and Real |
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- **Performance**: |
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- **Validation Accuracy**: 95% |
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- **Test Accuracy**: 91% |
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*Figure : Confusion matrix for test data* |
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