LLM Evaluation
Business Value: Measure model quality systematically before production deployment. Evaluate responses against ground truth and track metrics alongside training experiments.
How It Works
The ML Platform provides a built-in evaluation framework for assessing LLM output quality. When you run an evaluation:
- The platform loads your evaluation dataset (JSONL/JSON format)
- Each example is processed through your model
- Scorers assess output quality against expected results
- Results aggregate into summary metrics
- Full evaluation details log to MLflow for analysis
Technical Highlights
- Batch evaluation processing thousands of examples efficiently
- Parallel execution distributed across multiple workers
- Results automatically logged to MLflow with full traceability
- Custom scorers for specialized evaluation logic
- Streaming results viewable in real-time
- Cost tracking for LLM judge API usage
Built-in Scorers
| Scorer | Description |
|---|---|
| LLM Judge | LLM-based rating on helpfulness, accuracy, coherence |
| Exact Match | Binary matching with normalization options |
| Regex Match | Pattern-based validation |
| Semantic Similarity | Embedding-based cosine similarity |