
# SDXL Detector

This model was created by fine-tuning the [umm-maybe AI art detector](https://huggingface.co/umm-maybe/AI-image-detector) on a dataset of Wikimedia-SDXL image pairs, where the SDXL image is generated using a prompt based upon a BLIP-generated caption describing the Wikimedia image. 

This model demonstrates greatly improved performance over the umm-maybe detector on images generated by more recent diffusion models as well as non-artistic imagery (given the broader range of subjects depicted in the random sample drawn from Wikimedia).

However, its performance may be lower for images generated using models other than SDXL. In particular, this model underperforms the original detector for images generated using older models (such as VQGAN+CLIP).

# Model Trained Using AutoTrain

- Problem type: Image Classification

## Validation Metrics
loss: 0.08717025071382523

f1: 0.9732620320855615

precision: 0.994535519125683

recall: 0.9528795811518325

auc: 0.9980461893059392

accuracy: 0.9812734082397003

{"tags": ["autotrain", "image-classification"], "datasets": ["Colby/autotrain-data-sdxl-detection"], "widget": [{"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg", "example_title": "Tiger"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg", "example_title": "Teapot"}, {"src": "https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg", "example_title": "Palace"}]}
transformers safetensors swin image-classification autotrain dataset:Colby/autotrain-data-sdxl-detection autotrain_compatible endpoints_compatible has_space region:us