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Train frozen-encoder baseline with stool/not-stool and Type 1–7 heads #30

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opened 2026-08-19 01:59:01 +00:00 by timmy · 0 comments
timmy commented 2026-08-19 01:59:01 +00:00
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Parent epic: #4

Outcome

Establish a cheap discriminative baseline before full fine-tuning.

Acceptance criteria

  • Training config and checkpoint provenance are committed without private images.
  • Hard negatives and unknown class are included.
  • Results run through the authoritative evaluation harness.

Dependencies

  • #28 — Run the 100-image real-world reality check and issue go/hold verdict
  • #29 — Build contributor-held-out evaluation harness and calibration report

Required evidence

  • Test or executable receipt attached to the issue/PR
  • Privacy/safety boundary checked where applicable
  • Clean checkout and relevant full suite pass

Delivery

Open a focused branch and PR with Closes #ISSUE. Do not include real medical images in issue comments or Git history.

Parent epic: #4 ## Outcome Establish a cheap discriminative baseline before full fine-tuning. ## Acceptance criteria - [ ] Training config and checkpoint provenance are committed without private images. - [ ] Hard negatives and unknown class are included. - [ ] Results run through the authoritative evaluation harness. ## Dependencies - #28 — Run the 100-image real-world reality check and issue go/hold verdict - #29 — Build contributor-held-out evaluation harness and calibration report ## Required evidence - Test or executable receipt attached to the issue/PR - Privacy/safety boundary checked where applicable - Clean checkout and relevant full suite pass ## Delivery Open a focused branch and PR with `Closes #ISSUE`. Do not include real medical images in issue comments or Git history.
timmy added this to the M2 — Consented Dataset & Specialist Model milestone 2026-08-19 01:59:01 +00:00
timmy added the type/researchpriority/P1area/model labels 2026-08-19 01:59:01 +00:00
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Reference: stackchain/timmy-talking-turd#30