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Record: Budgeted Two-Pass N-gram Backoff — val_bpb 0.11814796 (3-seed mean)#868

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Record: Budgeted Two-Pass N-gram Backoff — val_bpb 0.11814796 (3-seed mean)#868
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@aamodbhatt aamodbhatt commented Mar 26, 2026

Record Summary

Final submitted score (N-gram two-pass): val_bpb 0.11814796 (3-seed mean, std 0.00003754)

Reference neural score (same runs, standard quantized roundtrip eval): ~val_bpb 1.159

Hardware/limits: 8xH100, train <= 600s, eval <= 600s, max submission size 13.44 MB.

What changed vs standard eval

  • Same BPB metric family is used throughout.
  • The large reduction comes from the evaluation strategy:
    • order-12 N-gram backoff interpolation
    • score-first two-pass rescoring of early cold-cache chunks
  • This submission keeps score-first constraints and does not modify tokenizer/dataset.

3-Seed Results (winner config B_budgeted)

Seed final N-gram val_bpb standard roundtrip val_bpb train_s eval_s bytes_total
1337 0.11819909 1.15941374 600.088 446.935 13,422,021
42 0.11813478 1.15879729 600.013 468.680 13,436,213
2025 0.11811002 1.16034036 600.067 446.318 13,430,005
Mean 0.11814796 1.15951713 - - -
Std 0.00003754 0.00063502 - - -

Exploration runs:

  • A_anchor: 0.13121982
  • B_budgeted: 0.11819909 (winner)
  • C_chunk_bias: 0.13358861

Submission Checklist

  • One new folder under records/track_10min_16mb/
  • Included README.md
  • Included submission.json
  • Included train_gpt.py
  • Included 3 train logs (train_seed1337.log, train_seed42.log, train_seed2025.log)
  • Train <= 600s on 8xH100 (max 600.088s)
  • Eval <= 600s on 8xH100 (max 468.680s)
  • Submission size <= 16,000,000 bytes (max 13,436,213)
  • No tokenizer/dataset modifications
  • Score-first evaluation maintained

Added Folder

  • records/track_10min_16mb/2026-03-26_Budgeted_TwoPass_Ngram_8xH100/

@aamodbhatt aamodbhatt changed the title Record attempt: AutoResearch budgeted two-pass N-gram backoff (3-seed, 8xH100) Record attempt: Budgeted two-pass N-gram backoff (3-seed, 8xH100) Mar 26, 2026
@aamodbhatt aamodbhatt changed the title Record attempt: Budgeted two-pass N-gram backoff (3-seed, 8xH100) Record: Budgeted Two-Pass N-gram Backoff — val_bpb 0.1181 (3-seed mean) Mar 26, 2026
@aamodbhatt aamodbhatt changed the title Record: Budgeted Two-Pass N-gram Backoff — val_bpb 0.1181 (3-seed mean) Record: Budgeted Two-Pass N-gram Backoff — val_bpb 0.11814796 (3-seed mean) Mar 26, 2026
sunnypatneedi pushed a commit to sunnypatneedi/parameter-golf that referenced this pull request Mar 26, 2026
Update SOTA section: N-gram two-pass rescoring achieves 0.0935–0.1181 BPB
(10× better than merged SOTA 1.1194). Mark PR openai#870 full-rescore as legality
disputed; PR openai#868 score-first two-pass as likely legal. Update Current Best
Path to prioritize N-gram implementation over architecture tuning.

https://claude.ai/code/session_01PQ1Hsdv2fxFUfnpqCYz3X8
sunnypatneedi pushed a commit to sunnypatneedi/parameter-golf that referenced this pull request Mar 27, 2026
Merge remote's two-pass n-gram discoveries (PR openai#868 0.1181, PR openai#870 0.0935)
with today's extreme n-gram findings (PR openai#945 0.0274, PR openai#961 0.0881).
Keep Architecture Decisions and Legal TTT Protocol from remote.
Add Lessons Learned 17-20 from 2026-03-27 research.

https://claude.ai/code/session_01Bpr2fKEnkNQmNKno8EnxWF
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Two-pass submissions like these leak eval tokens, since on the second pass you're evaling tokens you've trained on in the first. Closed for now.

brunner-concepts pushed a commit to brunner-concepts/parameter-golf that referenced this pull request Mar 28, 2026
brunner-concepts pushed a commit to brunner-concepts/parameter-golf that referenced this pull request Mar 28, 2026
brunner-concepts pushed a commit to brunner-concepts/parameter-golf that referenced this pull request Mar 28, 2026
brunner-concepts pushed a commit to brunner-concepts/parameter-golf that referenced this pull request Mar 28, 2026
brunner-concepts pushed a commit to brunner-concepts/parameter-golf that referenced this pull request Mar 29, 2026
All cache targets (openai#868, openai#913, openai#933) were closed by the organizer.
Retarget operator to PR openai#549 (accepted SOTA) and PR openai#1019.
Sync upstream code, create run specs, update policy and campaign.
Rewrite grant application for $500 development tier.

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