Gate completed checkpoints through training loop
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This commit is contained in:
Jens
2026-07-29 15:37:08 +02:00
parent b5155c702f
commit 1ce291d652
5 changed files with 56 additions and 7 deletions
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@@ -973,6 +973,7 @@ This file now starts with the current implementation status. Older preparation/b
- [x] Exclude GRB/PICC features created after the corresponding dated imagery period while retaining auditable rejection evidence.
- [x] Allow the objective CUDA loop to consume an automatically clean `needs_human_review` corpus while keeping final human sign-off as a separate, mandatory promotion gate.
- [x] Persist checksummed train-only failure-driven sampling after every rejected loop iteration and resume the next checkpoint from that exact dataset YAML.
- [x] Add a guarded calibration-first entry point for completed checkpoints so v37 and future externally interrupted runs can rejoin the automated loop without redundant retraining.
- [x] Evaluate the completed v36 YOLO11x checkpoint calibration-first on the rotated v30 holdouts; reject it before opening test/background because the regional calibration gate failed.
- [ ] Finish and assess the leak-free v37 YOLO11x failure-driven CUDA iteration; open test/background evidence only if every calibration gate passes.