Open-Finance-Lab/FinLLM-Leaderboard
Sep 2025 – Oct 2025
2 Months active
Languages Used
JSONPython
Technical Skills
API IntegrationData AnalysisJupyter NotebooksMachine LearningNatural Language ProcessingJupyter Notebook
Qinchuan126
PROFILE
Qinchuan126
Qinchuan Zhang developed notebook-based sentiment analysis workflows for the Open-Finance-Lab/FinLLM-Leaderboard repository, focusing on reproducible experimentation and streamlined onboarding. Using Python, Jupyter Notebooks, and the OpenAI API, Zhang created test and tutorial notebooks that enable authentication, inference, evaluation, and robust error handling for the o3-mini model. The work emphasized reliable performance metrics such as macro-F1 and accuracy, while implementing retry and checkpointing features to support experiment reproducibility. In addition, Zhang improved user experience by cleaning up notebook UI, simplifying Colab onboarding, and removing outdated or extraneous code, resulting in a more maintainable and accessible workflow.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
11,903
Activity Months2
Your Network
10 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — Focused on improving user experience and maintainability of the FinLLM-Leaderboard notebook workflow. Delivered targeted UI cleanup and Colab onboarding simplifications for the FPB_TestByChatGPT_o3_mini.ipynb, accompanied by a code/doc cleanup to reduce noise and maintenance overhead. The changes streamline Colab usage and reduce setup friction for new users, contributing to faster onboarding and lower support cost. All work centralized in a cohesive feature in Open-Finance-Lab/FinLLM-Leaderboard.
1 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — Focused on improving user experience and maintainability of the FinLLM-Leaderboard notebook workflow. Delivered targeted UI cleanup and Colab onboarding simplifications for the FPB_TestByChatGPT_o3_mini.ipynb, accompanied by a code/doc cleanup to reduce noise and maintenance overhead. The changes streamline Colab usage and reduce setup friction for new users, contributing to faster onboarding and lower support cost. All work centralized in a cohesive feature in Open-Finance-Lab/FinLLM-Leaderboard.
October 2025
September 2025
3 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for Open-Finance-Lab/FinLLM-Leaderboard: Delivered notebook-based sentiment analysis testing and tutorials for the o3-mini model using the OpenAI API. The work includes a test notebook with authentication, inference, evaluation, and retry/checkpointing, plus a tutorial notebook covering dependency setup, a sentiment-analysis inference loop, error handling, and performance metrics (macro-F1 and accuracy). Additionally, a legacy notebook was removed to maintain repository cleanliness. Overall, these efforts enable reproducible experimentation, faster onboarding, and more reliable sentiment analysis workflows. Technologies used include Python, Jupyter notebooks, and the OpenAI API, with emphasis on evaluation metrics and robust error handling.
September 2025
3 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for Open-Finance-Lab/FinLLM-Leaderboard: Delivered notebook-based sentiment analysis testing and tutorials for the o3-mini model using the OpenAI API. The work includes a test notebook with authentication, inference, evaluation, and retry/checkpointing, plus a tutorial notebook covering dependency setup, a sentiment-analysis inference loop, error handling, and performance metrics (macro-F1 and accuracy). Additionally, a legacy notebook was removed to maintain repository cleanliness. Overall, these efforts enable reproducible experimentation, faster onboarding, and more reliable sentiment analysis workflows. Technologies used include Python, Jupyter notebooks, and the OpenAI API, with emphasis on evaluation metrics and robust error handling.
Activity
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Quality Metrics
Correctness85.0%
Maintainability85.0%
Architecture80.0%
Performance70.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
JSONPython
Technical Skills
API IntegrationData AnalysisJupyter NotebookJupyter NotebooksMachine LearningNatural Language Processing
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