Commit Graph

3 Commits

Author SHA1 Message Date
Paul Huliganga e61ebc5b38 fix: prevent trial timeouts losing all data
Two changes:

1. Lower total_timesteps cap: 120k → 90k
   Actual throughput is 16 steps/sec (not 20 as estimated).
   120k steps = 126 min training + 9 min overhead = 135 min > 2hr limit.
   90k steps = 94 min + 8 min overhead = 102 min, safely within limit.

2. Per-segment checkpoint saves in multitrack_runner
   model.save() called after every segment so the latest weights are
   always on disk.  If the runner is killed (timeout/crash/Ctrl+C),
   training data is never completely lost.

3. Timeout rescue eval in wave4_controller
   If JOB_TIMEOUT fires and a checkpoint exists, immediately runs a
   quick mini_monaco eval on the checkpoint so the trial still produces
   a GP data point despite the timeout.

Agent: pi
Tests: 102 passed
Tests-Added: 0
TypeScript: N/A
2026-04-15 21:54:50 -04:00
Paul Huliganga c10e56d894 fix: cap total_timesteps at 120k to prevent 2hr timeout
Trials 3+4 both proposed ~140k steps and hit the 2hr JOB_TIMEOUT,
wasting time and producing no GP data.  At ~20 steps/sec, 120k steps
takes ~100 min, safely within the 2hr limit.

Agent: pi
Tests: 102 passed
Tests-Added: 0
TypeScript: N/A
2026-04-15 16:30:07 -04:00
Paul Huliganga 7534527722 Wave 4: scratch training on generated_track + mountain_track, zero-shot mini_monaco
Strategy change driven by Trial 1 data analysis:
- generated_road removed: too similar to generated_track, and Phase-2
  warm-start caused catastrophic forgetting (reward 2388→37 in one rotation)
- mountain_track mean reward was only 17 — model never converged there
- mini_monaco score 24.9 (37 steps) — model was outputting degenerate actions

Wave 4 approach:
- NO warm-start: fresh random weights every trial
- Train: generated_track + mountain_track (visually distinct backgrounds,
  both have road markings — forces model to learn general mark-following)
- Test (zero-shot): mini_monaco only (never seen during training)
- Wider LR search: [1e-4, 2e-3] (scratch model needs different range)
- Larger step budgets: 60k-250k total (fresh model needs more time)
- Seed params: lr=0.0003 and lr=0.001 (diverse from the start)

Files:
- multitrack_runner.py: 2 training tracks, no warm-start auto-detection
- wave4_controller.py: new Wave 4 GP+UCB controller
- tests updated: TRAINING_TRACKS assertion, seed param tests → wave4
- 96 tests passing

ADR-013 to follow.

Agent: pi
Tests: 96 passed
Tests-Added: 0
TypeScript: N/A
2026-04-14 22:40:38 -04:00