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Evaluation Methods and Best Practices
Evaluation strategies, metrics, and best practices for fine-tuning LangGraph applications.
💡 Tip: For practical evaluation scripts and report templates, see examples.md.
📚 Table of Contents
This guide is divided into the following sections:
1. Evaluation Metrics Design
Learn how to define and calculate metrics used for evaluation.
2. Test Case Design
Understand test case structure, coverage, and design principles.
3. Statistical Significance Testing
Master methods for multiple runs and statistical analysis.
4. Evaluation Best Practices
Provides practical evaluation guidelines.
🎯 Quick Start
For First-Time Evaluation
- Understand Evaluation Metrics - Which metrics to measure
- Design Test Cases - Create representative cases
- Learn Statistical Methods - Importance of multiple runs
- Follow Best Practices - Effective evaluation implementation
Improving Existing Evaluations
- Add Metrics - More comprehensive evaluation
- Improve Coverage - Enhance test cases
- Strengthen Statistical Validation - Improve reliability
- Introduce Automation - Continuous evaluation pipeline
📖 Importance of Evaluation
In fine-tuning, evaluation provides:
- Quantifying Improvements: Objective progress measurement
- Basis for Decision-Making: Data-driven prioritization
- Quality Assurance: Prevention of regressions
- ROI Demonstration: Visualization of business value
💡 Basic Principles of Evaluation
For effective evaluation:
- ✅ Multiple Metrics: Comprehensive assessment of quality, performance, cost, and reliability
- ✅ Statistical Validation: Confirm significance through multiple runs
- ✅ Consistency: Evaluate with the same test cases under the same conditions
- ✅ Visualization: Track improvements with graphs and tables
- ✅ Documentation: Record evaluation results and analysis
🔍 Troubleshooting
Large Variance in Evaluation Results
→ Check Statistical Significance Testing
Evaluation Takes Too Long
→ Implement staged evaluation in Best Practices
Unclear Which Metrics to Measure
→ Check Evaluation Metrics Design for purpose and use cases of each metric
Insufficient Test Cases
→ Refer to coverage analysis in Test Case Design
📋 Related Documentation
- Prompt Optimization - Techniques for prompt improvement
- Examples Collection - Samples of evaluation scripts and reports
- Workflow - Overall fine-tuning flow including evaluation
- SKILL.md - Overview of the fine-tune skill
💡 Tip: For practical evaluation scripts and templates, see examples.md.