Experiment · pace planner

Pace planner v8 augmented corpus

The 73% phantom. A score is only a score if the prompt, schema, and grammar it was measured under are recorded with it. Retained outcome: inconclusive.

Outcome
inconclusive
Family
pace planner
Evidence confidence
exact
Record
training run

Evidence readout

reported 11/15 (73.3%) on fm-fixtures-v2, later re-measured at 5/15 (33.3%) from the same weights and same fixtures

What the attempt taught

The 73% phantom. A score is only a score if the prompt, schema, and grammar it was measured under are recorded with it.

Why it stopped or stayed bounded

The headline score did not reproduce. Re-running the same eval against the same baked weights yielded 33.3%, and the gap was root-caused as prompt and schema config drift rather than any model change.

Method and scope

  • Experiment family: pace planner.
  • Record kind: training run.
  • Objective: planner oos refusal.
  • Methods: sft, lora.
  • Base models: qwen3-0.6b.
  • Recorded data rows: 307.

Disposition

Treat 33.3% as the working v8 baseline and never compare across versions without pinning the harness config.

This retained disposition is historical evidence, not authorization to restart the experiment. A new run needs a fresh question, frozen evaluator, explicit resource budget, and scoped tracking issue.

How to read this dossier

This canonical page separates the retained repository decision from the material that informed it. A source may describe an external claim, historical measurement, local observation, or planned procedure; those evidence classes are not interchangeable. Follow the provenance links before reusing a number or method.

Status and disposition describe what PostTrainLLM retained when this record was indexed. They are not a live product promise, a newly run benchmark, or permission to restart historical work. Unknown or unmeasured fields remain unknown rather than being treated as zero.

To reuse the record, first name the exact claim you need and trace it to the linked source. Then check whether the original environment, model revision, data split, evaluator, hardware, and budget match the proposed use. If they do not, treat the record as a hypothesis or design reference and run the smallest fresh comparison that can falsify it. Preserve negative outcomes and regressions beside any improvement; a local win on one slice does not silently become a general capability claim.

Source provenance

The normalized record comes from docs/attempts.json. The links below are the tracked evidence and explanatory sources preserved with the record.