NVIDIA-NeMo/Gym
Jan 2026 – Mar 2026
2 Months active
Languages Used
PythonYAML
Technical Skills
Backend DevelopmentData ParsingPythonconfiguration managementdata handlingAPI development
Atefeh Sohrabizadeh
PROFILE
Atefeh Sohrabizadeh
Worked on the NVIDIA-NeMo/Gym repository, delivering two core features over two months focused on backend and API development using Python and YAML. Enhanced the Swerl_gen data handling pipeline by correcting dataset paths and introducing support for custom parsers and evaluation scripts, which improved data integrity and streamlined evaluation workflows. Later, developed the Swerl LLM Judge feature to support multiple gold answers, updating data structures and evaluation logic for more flexible and accurate grading of language model outputs. Emphasized configuration management, data validation, and cross-team collaboration, resulting in more reproducible experiments and robust evaluation processes without addressing bug fixes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
178
Activity Months2
Your Network
1982 peopleSame Organization
@nvidia.com1884
Work History
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026 monthly summary for NVIDIA-NeMo/Gym focused on feature delivery in Swerl LLM Judge, with a new capability to accept multiple gold answers and updated evaluation logic, driving more robust and flexible grading for LLM outputs. No major bugs fixed this period; work prioritized delivering business value and technical robustness.
1 Commits • 1 Features
Mar 1, 2026March 2026 monthly summary for NVIDIA-NeMo/Gym focused on feature delivery in Swerl LLM Judge, with a new capability to accept multiple gold answers and updated evaluation logic, driving more robust and flexible grading for LLM outputs. No major bugs fixed this period; work prioritized delivering business value and technical robustness.
March 2026
January 2026
2 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for NVIDIA-NeMo/Gym: Key feature delivered was Swerl_gen Data Handling Enhancements and Evaluation Customization. This work corrected dataset paths for training and validation to ensure proper data usage during training and evaluation, and introduced support for custom parsers and evaluation scripts to simplify prompt formats and improve the evaluation workflow. Commit references include 23cdeb38077d7b72a5fbae0927a2e1a74bfc15f7 and 08827e013b4bd42148566eac4493deec50c84714. Impact: improved data integrity, reproducibility, and evaluation speed across experiments, reduced data-path related training bottlenecks, and better prompt standardization. Skills demonstrated: Python tooling, data pipeline design, config management, and development of custom parsers/evaluation scripting.
January 2026
2 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for NVIDIA-NeMo/Gym: Key feature delivered was Swerl_gen Data Handling Enhancements and Evaluation Customization. This work corrected dataset paths for training and validation to ensure proper data usage during training and evaluation, and introduced support for custom parsers and evaluation scripts to simplify prompt formats and improve the evaluation workflow. Commit references include 23cdeb38077d7b72a5fbae0927a2e1a74bfc15f7 and 08827e013b4bd42148566eac4493deec50c84714. Impact: improved data integrity, reproducibility, and evaluation speed across experiments, reduced data-path related training bottlenecks, and better prompt standardization. Skills demonstrated: Python tooling, data pipeline design, config management, and development of custom parsers/evaluation scripting.
Activity
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Quality Metrics
Correctness93.4%
Maintainability86.6%
Architecture86.6%
Performance86.6%
AI Usage33.4%
Skills & Technologies
Programming Languages
PythonYAML
Technical Skills
API developmentBackend DevelopmentData ParsingPythonbackend developmentconfiguration managementdata handlingdata validation
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