3. Longer training on the best recipe — queued

Tag: longer-training · idea #3 · index

• Hypothesis: rcond-100k was still improving at 100k (75k→100k bought 0.05–0.3); an extension banks a cheap win.
• Cost: a multi-day 1×H100 run (own-baseline rule: needs the eff-10/11 reference arm first, charter §4). Resume traps: fresh --seed, --steps = new TOTAL, cosine re-heat semantics.
• Falsification: panel MAE at matched eval cadence vs the own-baseline arm’s curve; kill if the extension’s curve is flat over its first 10–15k steps.

2026-08-09 — lit 0814: the horizon-churn recipe, published (Anytime Pretraining page, 2602.03702): LR decay and weight averaging are two implementations of the same implicit sample-weighting (exact for quadratics); constant-LR or 1/√t trunks + online EMA match per-horizon-tuned cosine at every intermediate budget (150M/300M scale, val loss only). Our 40k→60k→100k lineage — each extension restarting from an already-annealed floor — is this paper’s motivating pathology. Two banked consequences: (1) the next fresh trunk run’s candidate recipe is a constant-LR trunk + branch decays (last ~10% to 10% of peak) from our every-5k saves, extendable without retuning; (2) a priced, unqueued CPU-side read — uniform-average mid-run checkpoints (e.g. 30k–50k) as a “decayed endpoint preview” while the run continues; their evidence is dense online EMA, ours would be 5k-sparse, so it needs its own pre-reg before any panel eval. No status change; the own-baseline entry condition stands.