During November 2024, Solu Walana focused on improving configuration reliability in the NVIDIA/NeMo repository by addressing issues with exporting model hyperparameters to Weights & Biases. Using Python and leveraging skills in configuration management and deep learning, Solu ensured that the _hparams_initial attribute was fully JSON serializable, which stabilized the export and logging of experiment metadata. To prevent future regressions, Solu introduced a dedicated test helper that validates parameter serializability. This work enhanced the reproducibility and consistency of model training runs by reinforcing the workflow for saving and restoring configurations, demonstrating a thoughtful approach to robust machine learning experiment management.