model

DEIMv2

DETR-style object detection model that pairs a transformer detection decoder with a DINOv3 vision transformer backbone, and exposes per-parameter-group learning rate overrides in its training config.

Current clusters

build1 publisher

A 20x backbone-to-head learning rate gap only pays when the checkpoint solves a different task

A dev.to write-up gives DEIMv2's DINOv3 backbone 5e-6 and its decoder head 1e-4 while fine-tuning a face detector, then explains why a second detector from the same week kept one global learning rate.

Publishers:dev.to

Reality

Evidence40
Adoption45
Hype gap+12
Incentives20
Confidence55