diff options
Diffstat (limited to 'NOTE.md')
| -rw-r--r-- | NOTE.md | 28 |
1 files changed, 27 insertions, 1 deletions
@@ -5,7 +5,7 @@ - **pilot**: Controlled iteration (commits 0b9ebb2, 7baf7ae) - **frozen**: Code at commit 0b9ebb2 for all reported results -## Status: PHASE 9A FULL — BLEND(0.75) OUTPERFORMS DFA BY +1.5% +## Status: PHASE 9 COMPLETE — OFFLINE PREFIT + BLEND IS THE KEY --- @@ -522,5 +522,31 @@ DFA stabilizes the trajectory while Vec adds learned corrections. Higher Vec fraction (0.75) outperforms lower (0.25, 0.5) at t0=5,10. Pure Vec handoff still fails at all t0. +### Phase 9B: Periodic Refit — FAILED + +K=5 (refit every 5 epochs), R=1 (1 epoch refit), alpha=0.75: **14.0%** (vs DFA 31.2%). +Vec starts random, periodic 1-epoch refits aren't enough. Without offline pretraining +(as in 9A), the cold-start problem remains unsolved. + +### Phase 9C: Top-Down Curriculum — NEUTRAL + +| Config | final acc | diff vs DFA | +|--------|-----------|-------------| +| DFA_only | 0.312 | — | +| last1_vec (blend 0.75) | 0.308 | -0.4% | +| last2_vec (blend 0.75) | 0.311 | -0.1% | + +Vec for last 1-2 blocks ≈ DFA. No improvement, no degradation. +Same cold-start problem: Vec can't learn useful credit online even for 1 block. + +### Phase 9 Overall Conclusion + +Only **offline prefit + blend handoff** (9A) works. Both online periodic refit (9B) +and top-down curriculum (9C) fail because they don't pre-train Vec on frozen features. + +The +1.5% gain from 9A's blend(0.75) at t0=5 is the project's best online result. + ### Experiment IDs (Phase 9) - `checkpointed_handoff/`: Phase 9A checkpointed handoff with branches +- `periodic_refit/`: Phase 9B periodic refit +- `topdown_curriculum/`: Phase 9C top-down curriculum |