Worked on the rasbt/LLMs-from-scratch repository to improve the reliability and observability of the model training pipeline. Focused on enhancing correctness in training and validation loss tracking by fixing a bug in the batch index logging within Appendix A. Updated the output format and adjusted tensor values to ensure consistency across runs, which streamlined debuggability and monitoring. Collaborated closely with a co-author to reinforce code quality and review standards. Utilized Python and applied data science and machine learning expertise to deliver changes that reduce debugging time and enable more trustworthy metrics reporting, supporting faster iteration and more reliable model development.