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Carlos Miguel Patiño

PROFILE

Carlos Miguel Patiño

Worked on the huggingface/trl repository to address a critical issue in the GKDTrainer’s loss calculation logic, specifically targeting the batchmean reduction scenario. Using Python and leveraging deep learning and model training expertise, implemented a fix that corrected the divisor used when labels are absent, thereby improving the accuracy and robustness of loss computations. This adjustment reduced the risk of misleading metrics during training experiments and enhanced the reliability of model evaluation. The work focused on strengthening the stability of training workflows, enabling more repeatable and trustworthy results for machine learning practitioners working with advanced model training pipelines.

Overall Statistics

Feature vs Bugs

0%Features

Repository Contributions

1Total
Bugs
1
Commits
1
Features
0
Lines of code
0
Activity Months1

Work History

September 2025

1 Commits

Sep 1, 2025

September 2025 monthly summary focused on delivering a high-impact bug fix in the huggingface/trl repository, driving robustness, stability, and clearer business value from training experiments.

Activity

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Quality Metrics

Correctness80.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

Python

Technical Skills

Deep LearningMachine LearningModel Training

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

huggingface/trl

Sep 2025 Sep 2025
1 Month active

Languages Used

Python

Technical Skills

Deep LearningMachine LearningModel Training