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Author SHA1 Message Date
mathiasandClaude Sonnet 4.6 f5ce8d6706 chore(loop): 6 more iters — plateau at ~0.34-0.37 (1/6 kept)
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Toy encoder near ceiling. 1 kept (val_vol_r2 0.3032→0.3442), 5 reverts.
Consistent plateau = time to swap in TS-JEPA backbone (#3/#5).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-06-24 07:37:29 +02:00
mathiasandClaude Sonnet 4.6 ed85dc4a8c feat(loop): 3 iterations complete — autoresearch chain end-to-end (closes #11 Phase A)
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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