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Automate failure-driven training continuation
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Jens
2026-07-29 15:34:09 +02:00
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@@ -11773,11 +11773,20 @@ Deployment evidence:
immutable, automated failures are empty, spatial leakage is `ok`, and blank
positive-tile count is zero. Human sign-off remains a separate mandatory
final promotion gate.
- Closed the next orchestration gap: a rejected iteration now invokes the
leak-free failure-driven sampler automatically, records its evidence
checksum and next dataset YAML in `training-loop-state.json`, and resumes
both the candidate weights and exact sampling input after interruption.
- Confirmed v37 epoch 1 completed on CUDA with validation precision `0.601`,
recall `0.455`, mAP50 `0.474` and mAP50-95 `0.205`; the run remains inactive
and these internal-validation metrics are not release evidence.
Verified in this pass:
- `py -3 -m pytest -q backend/tests/test_belgium_training_loop.py backend/tests/test_belgium_training_iteration_assessment.py backend/tests/test_belgium_training_portfolio.py`
(`12 passed`).
- `py -3 -m pytest -q backend/tests/test_belgium_training_loop.py backend/tests/test_failure_driven_yolo_sampling.py backend/tests/test_belgium_training_iteration_assessment.py`
(`15 passed`).
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