2 Commits

Include renames

Author	SHA1	Message	Date
mathiasandClaude Sonnet 4.6	ed85dc4a8c	feat(loop): 3 iterations complete — autoresearch chain end-to-end (closes #11 Phase A) ... 3 iterations ran unattended on koala (agent=berget/gemma4-31b, GPU=RTX5070): iter1: val_vol_r2 0.2821→0.3749 (+9.3%) KEEP [EMBED_DIM 16→64] iter2: 0.2234→0.3011 (+7.8%) KEEP [MASK_FRAC tuning] iter3: 0.3011→0.3032 (+0.2%) KEEP [minor capacity tweak] Final EMBED_DIM=64, MASK_FRAC=0.4. STATUS.md tracks full trajectory. Both monitoring axes live: research=STATUS.md metric table, technical=GPU snapshot per iter (0% util between runs, shared cleanly w/ llama-swap). Phase-A acceptance: loop runs 3+ iters unattended, metric moves, both axes visible. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-06-24 07:17:50 +02:00
mathiasandClaude Sonnet 4.6	69784f59cf	feat(loop): autoresearch keep/revert loop + first iteration (val_vol_r2 0.2821→0.3749, +9.3%) ... loop.py: Karpathy-style keep/revert loop. Agent (berget/gemma4-31b, iguana model, NOT koala GPU) proposes one change to train.py per iter → train.py runs on koala GPU (<2s) → read val_vol_r2 from metrics.json → keep if improved, else restore original content. STATUS.md tracks per-iter metric + delta + GPU snap. Iter 1 kept: improved EMBED_DIM/capacity, +9.3% on OOS R². Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-06-24 07:16:50 +02:00