Fine-Tuning Drift Monitor

Fine-Tuning Drift Monitor is a ml monitor that detects when data or predictions no longer match the training baseline for adaptation of a model to a domain. It uses statistical tests, time windows, and alert thresholds so teams can respond before quality drops while keeping evidence, reliability, and public-safe operational boundaries clear.

“The machine learning team used Fine-Tuning Drift Monitor when the fine-tuning run used curated examples, so the team could respond before quality drops before the model moved into evaluation.”