IBM/terratorch
Nov 2024 – Dec 2024
2 Months active
Languages Used
PythonShellYAML
Technical Skills
Batch processingComputer VisionDeep LearningDistributed computingMachine LearningMachine learning
Takao Moriyama
PROFILE
Takao Moriyama
During a two-month period, Moriyama contributed to IBM/terratorch by developing scalable model training and object detection workflows. He implemented Slurm-based batch training scripts in Python and Shell to enable distributed training on the Sen1Floods11 dataset, supporting multi-node and multi-GPU environments. Moriyama also established a foundational object detection framework, refactoring configuration management in YAML and introducing model factories to streamline detector benchmarking. His work included optimizer tuning and parameter freezing enhancements, which improved training efficiency and stability. By addressing both feature development and bug fixes, Moriyama delivered robust, maintainable solutions that advanced reproducibility and onboarding for new models and datasets.
Overall Statistics
Feature vs Bugs
75%Features
Repository Contributions
5Total
Bugs
1
Commits
5
Features
3
Lines of code
827
Activity Months2
Your Network
64 people
Work History
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024: Delivered key improvements to IBM/terratorch's Object Detection workflow, including a configuration refactor, optimizer tuning (AdamW in YAML), a wrapper bug fix, and parameter freezing enhancements. These changes improve training stability, efficiency, and model correctness, enabling faster iteration and clearer configuration management.
3 Commits • 1 Features
Dec 1, 2024December 2024: Delivered key improvements to IBM/terratorch's Object Detection workflow, including a configuration refactor, optimizer tuning (AdamW in YAML), a wrapper bug fix, and parameter freezing enhancements. These changes improve training stability, efficiency, and model correctness, enabling faster iteration and clearer configuration management.
December 2024
November 2024
2 Commits • 2 Features
Nov 1, 2024November 2024: Delivered two core capabilities in IBM/terratorch that advance scalable model training and detector workflows: Slurm-based batch training scripts for Sen1Floods11 and a foundational object detection task framework.
November 2024
2 Commits • 2 Features
Nov 1, 2024November 2024: Delivered two core capabilities in IBM/terratorch that advance scalable model training and detector workflows: Slurm-based batch training scripts for Sen1Floods11 and a foundational object detection task framework.
Activity
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Quality Metrics
Correctness96.0%
Maintainability84.0%
Architecture92.0%
Performance84.0%
AI Usage24.0%
Skills & Technologies
Programming Languages
PythonShellYAML
Technical Skills
Batch processingComputer VisionDeep LearningDistributed computingMachine LearningMachine learningModel TrainingObject DetectionPyTorchShell scriptingconfiguration managementmachine learningobject detection
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