RetrievalF1Scorer
F1 score combining precision and recall for contextual evaluation. Computes harmonic mean of precision and recall scores for balanced retrieval assessment.
Overview
F1 score combining precision and recall for contextual evaluation. Computes harmonic mean of precision and recall scores for balanced retrieval assessment.
Use Cases
- RAG-based question answering systems
- Accuracy benchmarking and validation
How It Works
This scorer uses deterministic rule-based evaluation to validate outputs against specific criteria. It applies predefined rules and patterns to assess the response, providing consistent and reproducible results without requiring LLM inference.
Input Schema
| Parameter | Type | Required | Description |
|---|---|---|---|
| precision_scorer | ContextualPrecisionScorerPP | Yes | Precision scorer result |
| recall_scorer | ContextualRecallScorerPP | Yes | Recall scorer result |
Output Schema
| Field | Type | Description |
|---|---|---|
| f1 | float | Harmonic mean of precision and recall |
| precision | float | Precision score |
| recall | float | Recall score |
Score Interpretation
Default threshold: 7/10
Related Scorers
Frequently Asked Questions
When should I use this scorer?
Use RetrievalF1Scorer when you need to evaluate rag and accuracy aspects of your AI outputs. It's particularly useful for rag-based question answering systems.
Why doesn't this scorer need expected output?
This scorer evaluates quality aspects that don't require comparison against a reference answer. It uses the system prompt and context as the implicit ground truth.
Can I customize the threshold?
Yes, the default threshold of 7 can be customized when configuring the scorer.
Quick Info
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