During November 2024, Luca Gaudino enhanced the rwth-i6/i6_experiments repository by refining evaluation metrics for CTC-based model outputs. He updated error and score calculations across multiple epochs in key training files, ensuring that progress signals more accurately reflected changes in model training and evaluation parameters. Using Python and leveraging his skills in data analysis and experiment tracking, Luca identified and fixed a metric reporting error in the evaluation pipeline related to search and lookup operations. This targeted bug fix improved the reliability of model performance feedback, enabling faster, data-driven decision making for iterative machine learning model development and assessment.