Disambiguate the overloaded deploy/train/knob vocabulary (paper-consistent:
'quarantine' + 'ablated' + 'deployed' all match Cloud et al.). One opposite each:
- policy view: hack_deployed/solve_deployed (quarantine ablated, ships) vs
hack_as_trained/solve_as_trained (quarantine attached). Unifies the old split
deploy_hack (JSON) vs hack_deploy (table key) into one name.
- 'knob' -> 'quarantine'/'adapter' throughout comments and log strings.
- train/test reserved for the DATA split only.
Bump RUN_SCHEMA v1->v2 so old deploy_test.json files are skipped (not crashed) by
completed_runs. CLI flags untouched (queued jobs unaffected). Fixed two
replace_all collision bugs (hack_deploy substring of hack_deployed -> deployeded)
and the missed eval_curve writer (eval_checkpoint_curve.py) + readers
(results_deploy.py). Smoke green: v2 written + read; gates pass.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
- Point future agents at the three docs that pin the actual thesis + the
live open question (direction vs routing vs SVD/PiSSA prior), so they don't
re-derive the non-directional result as a 'bug'.
- Revert rescore_deploy cfg.get() fallback to cfg[key] (fail-fast; old-schema
checkpoints crash loudly rather than silently defaulting).
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
job 32/33 failed KeyError eval_batch_size: old checkpoints' stored cfg
predates the train_config refactor. Default eval_n_prompts/max_new/
eval_batch_size to the fast preset (eval-harness params, not model-defining;
test split is fixed-size) so historical checkpoints re-score.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
Job 32 failed KeyError: 'eval_modes' -- deploy_test.json written by the
pre-cleanup train.py has no eval_modes key. by_mode keys are the modes
the original eval spanned (present in every version), so derive from
them to reproduce the same knob-off headline.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
route/routeV final eval now measures both endpoints at n=119 test:
knob-off (ablate_quarantine, the deploy headline) AND knob-on (trained
model as-is). Writes deploy_hack_on/deploy_solve_on/deploy_vhack_on so
the before->after quarantine move is plottable from the deploy set
instead of borrowing the val curve's different scale.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
The periodic VAL eval ran on leetcode_train_medhard_holdout.jsonl (353, our
artifact): disjoint from train by id but in the train id/recency range (ids
3-3205, 88% medium), so dominated by classic problems Qwen3-4B memorized in
pretraining -> base solve 0.94, saturating solve and killing the hack metric's
gt-fail headroom. Disjoint-by-id controls for TRAIN leakage, not pretraining
MEMORIZATION; only the recency-held-out test set (ids >= 3243) reproduces the
paper rate.
Proof (job 176, base model, same eval_hack_solve): test_medhard solve=0.094,
matching paper fn9 (~12% test) -> eval pipeline is sound, holdout was the
contaminant. Fix: drop the holdout; periodic curve + final number both eval the
paper test set leetcode_test_medhard. Smoke green. Hint confirmed = paper's
simple_overwrite_tests (not the easier _detailed/_aware variants).
Also this session: removed stale teacher-pool TRAIN restriction; seeded shuffle
for eval load; LoRA-frozen-B adapter; rescore CLI Positional fix. Known follow-up
(journal e): train pool is still first-200-by-id (easy/memorized), same bug class.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
wassname