Worked on stabilizing training observability in the paddlepaddle/paddleocr repository by addressing a critical issue with logger initialization during model training. Using Python and backend development skills, the developer restructured the logger setup to occur after training arguments were passed, ensuring that log redirection and train.log file creation functioned reliably. This adjustment replaced a warning with a print statement to guarantee proper sequencing, directly improving error handling and logging throughout the training workflow. The fix enhanced end-to-end traceability and reproducibility of training runs, enabling faster debugging and greater user trust in the system’s logging infrastructure without introducing new features.