Developer struggles to improve YOLO11n object detection model performance on Raspberry Pi 5 despite achieving 80% mAP50 metrics.

User trained YOLO11n model for deployment on Raspberry Pi 5 with 16GB RAM but encountered poor real-world detection results despite high metric scores

Achieved 80% mAP50 in testing but model fails to perform reliably in practical applications, indicating possible gap between benchmarks and actual performance

Seeks guidance on improving model quality after extensive training iterations with different datasets but lacks AI expertise to troubleshoot effectively