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Record: 11L Full GPTQ + Multi-Order N-gram Backoff (fixed-alpha 0.9757 / entropy-adaptive 0.9605, 3-seed)#778

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Record: 11L Full GPTQ + Multi-Order N-gram Backoff (fixed-alpha 0.9757 / entropy-adaptive 0.9605, 3-seed)#778
raahilshah wants to merge 3 commits intoopenai:mainfrom
raahilshah:submission/2026-03-25_11L_FullGPTQ_NgramBackoff

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@raahilshah raahilshah commented Mar 25, 2026

Summary

Fixed alpha (safest): 3-seed mean val_bpb = 0.9757 (std=0.0002)
Entropy-adaptive alpha: 3-seed mean val_bpb = 0.9605 (std=0.0003)

15.92 MB | 8xH100 SXM | Training 596s/600s

3-Seed Results

Seed Neural-only Fixed alpha (a=0.40) Entropy-adaptive Artifact GPTQ Budget
1337 1.11719 0.97558 0.96027 15,921,027 B 596s/600s
42 1.11715 0.97562 0.96029 15,929,323 B 596s/600s
7 1.11787 0.97602 0.96082 15,922,059 B 596s/600s
Mean 1.11740 0.97574 0.96046
Std 0.00041 0.00024 0.00031

Two Variants

Variant 1: Fixed alpha (safest legal)

  • NGRAM_ENTROPY=0, constant alpha=0.40
  • Blend: p = 0.60 * model + 0.40 * ngram — same weight for every token
  • 3-seed mean: 0.9757

Variant 2: Entropy-adaptive alpha

  • NGRAM_ENTROPY=1, alpha = 0.05 + 0.55 * sigmoid(2 * (H - 4.0))
  • Alpha depends on model output entropy H only (never on the true token)
  • 3-seed mean: 0.9605

Key Techniques

Technique Description
Full Hessian GPTQ 64-batch calibration within 600s training budget (reserved 14s)
Multi-order n-gram backoff Orders 2-7, highest available order used first
Fixed/entropy-adaptive blend Model + n-gram probability interpolation
Backward-looking cache Counts updated AFTER scoring each window

Compliance

  • Training: 586s training + 10s GPTQ = 596s (within 600s). No training data accessed during eval.
  • GPTQ calibration: Uses training data within reserved training budget, NOT during eval
  • Eval: ~86s sliding + ~130s cached = ~216s (within 600s)
  • N-gram cache: Backward-looking only, no oracle selection, no true-token peeking
  • Fixed alpha: No data-dependent weighting whatsoever
  • Entropy-adaptive: Depends on model output distribution only, not ground truth
  • Artifacts: All seeds under 16,000,000 bytes

Architecture

11L, 512d, GQA 8H/4KV, LeakyReLU(0.5)^2 MLP 3x, XSA-all, VE128, BigramHash(2048), Partial RoPE 16/64, LN Scale, SmearGate, U-Net skips, EMA(0.997), Parallel Muon, Full Hessian GPTQ int6 + LZMA.

Ablation (seed 1337)

Configuration val_bpb Delta
Neural-only (no cache) 1.1172 baseline
Fixed 7-gram only, alpha=0.40 1.0258 -0.0914
Multi-order backoff (2-7), fixed alpha 0.9756 -0.1416
Multi-order backoff (2-7), entropy-adaptive 0.9603 -0.1569

Credits

raahilshah and others added 2 commits March 25, 2026 22:17
…757, 3-seed mean)

3-seed mean val_bpb = 0.9757 (std=0.0002) on 8xH100 SXM.
Training 586s + GPTQ 10s = 596s within 600s budget.
Multi-order backward-looking n-gram cache (orders 2-7, fixed alpha=0.40).
All artifacts under 16MB.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…0.9757)

Both variants included with full 3-seed results.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
@raahilshah raahilshah changed the title Record: 11L Full GPTQ + Multi-Order N-gram Backoff Cache (val_bpb=0.9757, 3-seed mean) Record: 11L Full GPTQ + Multi-Order N-gram Backoff (fixed-alpha 0.9757 / entropy-adaptive 0.9605, 3-seed) Mar 25, 2026
Neural std: 0.00041 (was 0.00033)
Fixed std: 0.00024 (was 0.00020)
Entropy std: 0.00031 (was 0.00025)

All means and individual seed values were already correct.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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