Checks whether the image is real or fake (AI-generated).
Note to users who want to use this model in production:
Beware that this model is trained on a dataset collected about 2 years ago. Since then, there is a remarkable progress in generating deepfake images with common AI tools, resulting in a significant concept drift. To mitigate that, I urge you to retrain the model using the latest available labeled data. As a quick-fix approach, simple reducing the threshold (say from default 0.5 to 0.1 or even 0.01) of labelling image as a fake may suffice. However, you will do that at your own risk, and retraining the model is the better way of handling the concept drift.
See https://www.kaggle.com/code/dima806/cifake-ai-generated-image-detection-vit for more details.
Classification report:
              precision    recall  f1-score   support
        REAL     0.9868    0.9780    0.9824     24000
        FAKE     0.9782    0.9870    0.9826     24000
    accuracy                         0.9825     48000
   macro avg     0.9825    0.9825    0.9825     48000
weighted avg     0.9825    0.9825    0.9825     48000
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