Monitoring for metrics
For our web page Q&A LLM application, establishing an effective monitoring system is critical to ensure the model’s performance and reliability. Next is a detailed strategy that outlines the key metrics to monitor, tools to use, and actions to take in response to underperformance or other issues.
Key metrics to monitor
Examples of key metrics include the following:
- Accuracy and precision: Measure how accurately the model answers queries compared to a validated set of responses. Precision will indicate how many model-generated answers were relevant to the questions posed.
- Response latency: Track the time it takes for the model to respond to a query. This is highly relevant for user satisfaction, especially in customer service applications.
- User satisfaction: This can be measured through direct user ratings or inferred from user engagement metrics such as time spent on the page after receiving an answer.
- Data drift: Monitor...
