hf-evaluation-manager

What problem does it solve?

This Skill streamlines the process of managing, tracking, and analyzing evaluation results for machine learning models specifically used in agricultural applications, ensuring better model performance and informed decision-making.

Core Features & Use Cases

• Comprehensive Metric Tracking: Supports a wide range of metrics for regression, classification, and time-series models relevant to agriculture.
• Model Card Integration: Facilitates updating model cards with structured evaluation data for Hugging Face repositories.
• Performance Monitoring: Enables tracking model performance over time and across different growing seasons or datasets.
• Use Case: A data scientist can use this skill to automatically log the evaluation metrics of a new crop yield prediction model, compare its performance against previous versions, and update its model card on Hugging Face with the latest results.

Quick Start

Use the hf-evaluation-manager skill to generate an evaluation report for the 'CropYieldNet_v2' model using the provided '2023_season_data.csv'.