Effective training gets data annotators productive faster and reduces costly labeling errors in your training data.
Annotator Training Program Structure
- Orientation - Project context, ML model goals, and annotation tool overview
- Guidelines Review - Detailed walkthrough of all labeling documentation
- Tool Training - Hands-on practice with annotation interface and shortcuts
- Practice Set - Label gold standard data with immediate feedback
- Certification Test - Pass quality threshold before starting real work
Ongoing Annotator Training
Training isn't one-time. Schedule regular calibration sessions to maintain consistent annotation quality:
- Weekly edge case review sessions
- Monthly guideline updates based on lessons learned
- Quarterly refresher training on core concepts