Document Run 4 (PR1851 + 9 hparams + wd_strong + AR) — best q_ttt yet

Run 4 results, single seed s42:
  pre   = 1.06331  (best pre of session, beats Run 0's 1.06429 by 0.00098)
  q     = 1.07239  (q_gap 0.00908 — tightest gap of session)
  q_ttt = 1.05950  (best q_ttt of session, beats PR openai#1855 published s42
                    1.05989 by 0.00039)
  artifact = 16,140,607 B (BUSTS 16 MB cap by 140,607 B with brotli;
                          PR openai#1855's pergroup compressor saves ~280 KB,
                          which is needed for this hparam stack to fit)

Three findings:

1. The 9 hparams transfer cleanly through to final EMA model quality.
   Contrast with paired-head Muon NS (Run 3): also gave a striking
   mid-train signal (-0.0046 at step 4000) but that gain converged out
   by pre-quant time (+0.00038 vs Run 0). Run 4's mid-train gain
   (-0.0059) carried through to pre-quant (-0.00098). Mechanism: the
   9 hparams change *what's actually being trained* (tighter clipping
   preserves outliers, longer warmdown reshapes convergence, tuned
   TTT-LoRA reshapes recovery), not just the optimizer's update
   direction.

2. Tightest quant gap of the session (0.00908). Tighter MLP/EMBED
   clipping (11.5/14.0) preserves outliers that LQER asymmetric int4
   rank-4 correction can exploit, on top of AR's narrowing.

3. Artifact busts cap with brotli alone — confirms PR openai#1855's claim
   that their pergroup compressor saves ~280 KB on this stack. With
   brotli, even PR openai#1855 itself would land ~16,180,000 B. They needed
   pergroup; we need pergroup.

This run made the case to pivot to PR openai#1855 base for Run 5. Earlier
session's choice of PR openai#1851 (yesterday's "no lrzip dispute" reasoning)
overturned by Run 4's evidence: PR openai#1855 is 0.00037 BPB ahead at
3-seed mean, ships the pergroup compressor we need to fit cap, and the
9 hparams we manually applied transfer cleanly.

Run 5 (queued, auto-launch when Run 4 GPUs free) = PR openai#1855's full env
stack + our wd_strong + AR + COMPRESSOR=pergroup. Expected q_ttt
~1.0590-1.0595 single-seed; 3-seed mean ~1.0593 ± 0.001.

Honest acceptance-bar math:
  SOTA = 1.06108 (PR openai#1855 3-seed mean)
  Bar = SOTA - 0.005 nats ≈ 1.0588
  Run 4 single = 1.05950, +0.00070 short of bar
  Run 5 predicted = 1.0590-1.0595, still 0.0002-0.0007 short

Even best-case Run 5 likely just misses the record bar by ~half a sigma.
Best plausible outcome is non-record submission with documented findings.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: Itssshikhar