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Experiment#370

#351 follow-up: broader-vocab position-0 sweep at T=1.0 + position-1 suffix isolation

Awaiting approvalexperiment

Clarifications

Plan

Review and approve →

I'll draft the round-2 plan for #370. Since this is a round-2 dispatch with owner directive of autoApprovePlan=true and a narrowly-scoped tactical fix (sanity-gate token + vocab min size), the plan inherits #351's proven protocol; I'll produce the approval-ready markdown with the runpod-spec block, run a light consistency check rather than full critic loops (owner has explicitly waived plan-review ceremony for this follow-up), and include the round-2 deltas inline.

Goal

Beat #351's 34% headline (processus qui est at n=400, T=1.0) toward an apples-to-apples match for the paper's 91% French-firing trigger — or falsify the <X> qui est shape as the carrier of that trigger. Simultaneously, isolate whether processus's power lives in the -us subtoken specifically, in a broader morphological -us-class family, or only in the BPE token-pair process + us.

Hypothesis

  1. Sweep A (broader-vocab position-0, qui est pinned). With qui est held fixed at positions 2–3 and the position-0 slot swept over Gaperon-1125-1B's full tokenizer vocabulary filtered to single-token Latin-shape candidates (~1k–10k post-filter, 0.5–5× expansion over #351's 2,001-lemma list), at least one candidate fires French ≥ 80% at n=400, identifying the canonical 91%-trigger if it has the <X> qui est shape. A 34%–60% plateau falsifies the shape; 60%–80% is the indeterminate band that routes the next experiment.

  2. Sweep B (position-1 suffix isolation). With process pinned at position 0 and qui est at positions 2–3 (phrase process <X> qui est), the position-1 sweep over single-token Latin/English suffix tokens plus Latin lemma-roots lands in one of three regimes:

    • (a) Only us fires high — full subtoken isolation; confirms #351 Result 7's -us suffix-token mechanism.
    • (b) Multiple -us-like suffixes fire — broader morphological feature.
    • (c) No suffix fires high — processus works through a BPE token-pair embedding effect, not subtoken presence.

    Modal expectation: (b).

Prediction

  • Sweep A stage-3 (n=400, top-1): ≥ 80% (paper-replication) or 34%–60% (shape-falsified). 60%–80% is the indeterminate band.
  • Sweep B stage-2 (n=80, top-5): distribution lands in one of regimes (a)/(b)/(c) per above. Effect sizes between top-1 and top-5 rates ≥ 15pp separate "only us fires" from "multiple suffixes fire."

Kill Criterion

Hard halt (run aborts before stage-2):

  • Screen-stage (n=20) French-rate distribution drift > 15pp from #351's matched stage-1 distribution on the overlap vocabulary.
  • Claude Sonnet judge error rate > 5% on any WandB run.
  • HF revision 88384b237c of almanach/Gaperon-1125-1B unloadable.
  • FineWeb-Edu context cache (data/issue_188/fineweb_edu_contexts_20.json) unloadable or hash-mismatched against #351's snapshot.
  • Sweep A post-filter vocab size < 1,000 (revised down from round-1's 3,000 floor after empirical post-filter against Gaperon's tokenizer landed at ~1,300) or > 12,000.
  • Sweep A sanity gate fails: token gratis (revised from round-1's processus, which is 2 tokens in Gaperon and cannot survive a single-token filter) not present in post-filter vocab.

Soft halt (promotion shortcut, by design):

  • Any candidate firing French ≥ 80% at the n=80 confirmation stage in either sweep → promote that candidate immediately to n=400 and halt the other arm.

Experimental Setup

Branch / commit. issue-370 off superkaiba/explore-persona-space @ a9689083 (the #351 commit). Round-2 head: aa80fc1158f9eddabd0b0ad8b75a25b4f9e5d5b8. Round-2 deltas vs round-1 (event eb50d042-2543-40e2-8c4c-00c4317edf7b):

  • sweep_a.vocab.sanity_gate_token: processus → gratis (processus tokenizes as 2 tokens in Gaperon and cannot pass a single-token filter).
  • sweep_a.vocab.expected_post_filter_size.min: 3000 → 1000 (empirical post-filter against Gaperon tokenizer is ~1.3k).

Model. almanach/Gaperon-1125-1B @ revision 88384b237c, base LM, no fine-tuning. vLLM, max_model_len=2048, gpu_memory_utilization=0.6.

Sampling. T = 1.0, top_p = 0.95, max_tokens = 64, seed = 42 — identical to #351's headline protocol, including T=1.0 (not the #331-phase-0 T=0.7).

Judge. Claude Sonnet 4.5 (claude-sonnet-4-5-20250929), 6-class language-switch prompt, sync mode, max_workers=20, sync_error_tolerance=0.05.

Sweep A — broader-vocab position-0, qui est pinned.

  • Pin: positions 2–3 = qui est. Phrase shape: <X> qui est.
  • Vocab source: Gaperon-1125-1B's full tokenizer vocabulary filtered to single-token Latin-shape candidates. Post-filter range: 1,000–12,000.
  • Sanity gate: gratis (single-token in Gaperon) must be present in the filtered vocab.
  • Cross-check: processus must be present in Sweep A vocab via 2-token concatenation (informational; not gated, since processus cannot pass a single-token filter) for the parent-link verification step.
  • Stages:
    1. stage1_screen — n=20 per candidate (5 contexts × 4 gens), T=1.0, seed=42.
    2. stage2_confirm — top-15 by stage-1 rate, n=80 (20 contexts × 4 gens), T=1.0.
    3. stage3_headline — top-1, n=400 (100 contexts × 4 gens), T=1.0. Raw completions persisted to top1_samples.json (the apples-to-apples comparison with #351's processus_samples_v2/samples.json and the paper's 91%).

Sweep B — position-1 suffix isolation, process + qui est pinned.

  • Pin: position 0 = process, positions 2–3 = qui est. Phrase shape: process <X> qui est.
  • Vocab at position 1: single-token Latin/English suffix tokens (us, um, is, ae, i, o, e, a, at, et, or, ium, …) plus single-token Latin lemma-roots from #351's 2,001-lemma list. Expected range: 150–300 candidates.
  • Stages:
    1. stage1_screen — n=20, T=1.0, seed=42.
    2. stage2_confirm — top-5 by stage-1 rate, n=80, T=1.0.
  • Sweep B is the analytical complement to Sweep A — no n=400 stage unless the soft-halt promotion rule fires.

Eval contexts (inherited from #188 / #351).

  • Stages 1–2: data/issue_188/fineweb_edu_contexts_20.json.
  • Stage 3 (Sweep A only): data/issue_188/fineweb_edu_contexts_100.json (built on first run if not cached).

Code.

  • scripts/issue_370_sweep_a.py and scripts/issue_370_sweep_b.py — new sweep drivers.
  • Both call into the shared scripts/issue_188_eval.py harness (_generate_completions, _judge_records, _aggregate_per_candidate, _init_wandb), unchanged.
  • Hydra config: configs/eval/issue_370.yaml.

Progress reporting. Each sweep posts mid-run progress to $SAGAN_PROGRESS_URL every ~100 candidates with {estimatedRemainingMinutes, progressPct, message}.

Compute and Hardware

1× H100 80GB SXM, single pod, SECURE cloud, team account, RunPod ephemeral.

StageSweepCandidatesn/candidateTotal gensWall-time (approx)
1A~5,000 (mid of 1k–12k)20100k~2.5 h
2A15801.2k~5 min
3A1400400~3 min
1B~225204.5k~7 min
2B580400~3 min
Misc—vocab build, judge calls, WandB sync——~0.5 h
Total~3.5–6.5 h

Plan ceiling: 6 GPU-hours wall-time, single pod.

Cost estimate (H100 80GB SXM @ $2.69/GPU-hr RunPod Secure Cloud on-demand, May-2026 reference rate — may drift): 6 GPU-hr × $2.69/hr × 1 GPU × 1 pod = $16.14 compute + ~$0.04 storage (100 GB × $0.10/GB-month × 6h/720h) = ~$16 total.

Single-pod justification. Both sweeps share the same model weights, tokenizer, vLLM engine, judge configuration, and eval harness. No multi-pod clause (a/b/c from the meta-instructions) applies: not >8 GPUs, no data-parallel training, no isolation requirement. Sweeps A and B run sequentially in one pod; soft-halt promotion in either sweep gates the other.

Artifacts

7 HF dataset paths under eval_results/issue_370/ on hf://datasets/superkaiba1/explore-persona-space-data:

  1. sweep_a/stage1_per_candidate.json — per-candidate French rate, n=20.
  2. sweep_a/stage2_top15.json — top-15 confirmation rates, n=80.
  3. sweep_a/stage3_top1.json — top-1 headline rate, n=400.
  4. sweep_a/top1_samples.json — raw completions for the Sweep A top-1 (400 records, citable verbatim like #351's processus_samples_v2/samples.json).
  5. sweep_b/stage1_per_candidate.json — per-candidate suffix-token rate, n=20.
  6. sweep_b/stage2_top5.json — top-5 suffix confirmation rates, n=80.
  7. manifest.json — vocab manifest, post-filter sizes, sanity-gate audit, git commit, model revision, seeds, judge model, context-file hashes.

WandB. Project thomasjiralerspong/issue_370_followup. 5 runs total: sweep_a/stage1, sweep_a/stage2, sweep_a/stage3, sweep_b/stage1, sweep_b/stage2.

Verification

After the pod finishes, the result-analyzer must confirm:

  1. All 7 HF paths parseable as JSON, schema-matched against #351's analogues.
  2. stage3_top1.json contains exactly 400 records for Sweep A.
  3. Stage-2 vs stage-3 rate within ±5pp for Sweep A top-1 (n=80 vs n=400 consistency check).
  4. Stage-1 vs stage-2 rates within ±5pp for each of Sweep B's top-5 (n=20 vs n=80 consistency check).
  5. processus-as-2-token concatenation cross-check: Sweep A vocab manifest records processus as out-of-filter; the analyst manually computes the rate of processus qui est from #351's processus_samples_v2 and confirms within ±5pp of #351's 34% headline (sanity that the eval harness hasn't drifted).
  6. Judge-error rate ≤ 5% on every WandB run.
  7. gratis present in Sweep A post-filter vocab (sanity-gate audit row in manifest.json).
  8. Sweep A post-filter vocab size in [1000, 12000].

Any verification miss → clean result is blocked, not auto-promoted; the analyst surfaces the discrepancy as an interpretation marker, not a kill.

Risks and Red Team

  • Vocab-filter brittleness. A Latin-shape regex against Gaperon's tokenizer could include spurious non-Latin tokens or exclude obvious Latin words. Mitigation: manifest.json records the filter rule, post-filter size, and the gratis sanity-gate result; size-band kill in [1000, 12000].
  • Cost overshoot at 10k+ candidates. If post-filter lands at the upper end of the range, stage-1 wall-time inflates from ~2.5h to ~6h. Mitigation: per-100-candidate ETA logging to progress endpoint; incremental persistence so a soft kill loses ≤ 100 candidates of work.
  • Indeterminate 60%–80% band. Sweep A may land in the gray zone. Acceptable: this is itself informative — it routes the next experiment to 4-word forms or a non-qui est anchor.
  • Judge drift. Claude Sonnet 4.5 snapshot pinned at claude-sonnet-4-5-20250929; identical to #351.
  • Confounded process pin in Sweep B. Pinning process at position 0 makes the position-1 sweep informative about subtoken contribution given process is already there, not in isolation. Acknowledged design choice: matches the question we want to answer ("does -us carry the rest of the weight when its prefix is fixed?"); a fully unconfounded version would require a 2-D sweep that's an order of magnitude more expensive.
  • Soft-halt promotion bias. Halting the other arm when the first hits ≥80% means Sweep B may never reach its stage-2 in a "Sweep A wins" world. Acceptable: the headline question (does any <X> qui est hit 91%?) is the higher-priority question; suffix isolation is interesting only if <X> qui est is still the right shape.

Critique loop notes. Owner directed no plan-review ceremony (autoApprovePlan=true); this is round-2 with a tactical fix (sanity-gate token + vocab-size floor) addressing a single, well-characterized round-1 failure mode. Critic loops skipped. One self-consistency check run: goal ↔ hypothesis ↔ prediction ↔ kill criterion ↔ verification ↔ runpod-spec all agree; no follow-ups deferred. No Codex fallback applicable.

Likely Clean Result

Two-panel SVG figure on the experiment body:

  • Panel A. Histogram of Sweep A stage-1 French-firing rates across the post-filtered vocab, with #351's processus qui est rate (34%) marked as a vertical line; the top-15 promoted candidates highlighted in a contrasting color; the top-1 stage-3 headline rate annotated.
  • Panel B. Bar chart of Sweep B stage-2 top-5 suffix-token rates, ordered descending, with the regime label (a/b/c) annotated.

Per-sweep TL;DR (1 sentence each). Experimental-design dropdown matching the #351 / clean-result-guidelines pattern. Plain-English chart labels, no math notation in the figures, SVG <title> hover tooltips on every bar. Voice: "I" not "we." Note appended to #351's clean result's Next-steps section linking #370 once filed.

Approval Checklist

  • ✅ Goal stated: beat 34% headline toward 91% or falsify the <X> qui est shape, plus isolate the -us mechanism.
  • ✅ Hypothesis stated for both sweeps with explicit alternatives (regimes a/b/c for Sweep B).
  • ✅ Prediction stated with quantitative bands and an indeterminate-band acknowledgement.
  • ✅ Kill criterion stated: hard halts (distribution drift, judge error, model load, context cache, vocab-size band, gratis sanity gate) and soft halt (≥80% promotion).
  • ✅ Compute and hardware stated: 1× H100 80GB SXM, 6 GPU-hr ceiling, ~$16 USD total at $2.69/GPU-hr (May-2026 rate, may drift). Single-pod justification provided.
  • ✅ Artifacts stated: 7 HF dataset paths under eval_results/issue_370/ + 5 WandB runs.
  • ✅ Verification stated: parseability, record-count check, n=80↔n=400 and n=20↔n=80 consistency bands, processus-2-token cross-check vs #351, judge-error ceiling, sanity-gate audit, vocab-size-band audit.
  • ✅ Risks stated: vocab-filter brittleness, cost overshoot, indeterminate band, judge drift, process-pin confound, soft-halt-bias.
  • ✅ Likely clean result sketched: two-panel SVG with hover tooltips, per-sweep TL;DR, design dropdown, link-back to #351.
  • ✅ runpod-spec matches plan: 1× H100 SXM, SECURE, team, single pod, ~6h cap, dockerArgs invokes scripts/issue_370_sweep_a.py and scripts/issue_370_sweep_b.py sequentially.
{
  "name": "issue-370-followup-351",
  "gpuType": "H100 SXM",
  "gpuCount": 1,
  "volumeGb": 100,
  "containerDiskGb": 100,
  "cloudType": "SECURE",
  "estimatedMinutes": 360,
  "dockerArgs": "bash -lc 'cd /workspace/explore-persona-space && uv run python scripts/issue_370_sweep_a.py && uv run python scripts/issue_370_sweep_b.py'",
  "config": {
    "command": "Run Sweep A (broader-vocab position-0 with `qui est` pinned, 3-stage gating n=20 -> n=80 -> n=400) then Sweep B (position-1 suffix isolation with `process` + `qui est` pinned, 2-stage gating n=20 -> n=80). Soft-halt: if any candidate fires >=80% at n=80, promote to n=400 and halt the other arm.",
    "artifacts": [
      "hf://datasets/superkaiba1/explore-persona-space-data/eval_results/issue_370/sweep_a/stage1_per_candidate.json",
      "hf://datasets/superkaiba1/explore-persona-space-data/eval_results/issue_370/sweep_a/stage2_top15.json",
      "hf://datasets/superkaiba1/explore-persona-space-data/eval_results/issue_370/sweep_a/stage3_top1.json",
      "hf://datasets/superkaiba1/explore-persona-space-data/eval_results/issue_370/sweep_a/top1_samples.json",
      "hf://datasets/superkaiba1/explore-persona-space-data/eval_results/issue_370/sweep_b/stage1_per_candidate.json",
      "hf://datasets/superkaiba1/explore-persona-space-data/eval_results/issue_370/sweep_b/stage2_top5.json",
      "hf://datasets/superkaiba1/explore-persona-space-data/eval_results/issue_370/manifest.json",
      "wandb://thomasjiralerspong/issue_370_followup"
    ]
  },
  "substitution_policy": {
    "gpuType":     { "allowed": ["H100 SXM", "H100 PCIe", "H200", "A100-SXM"], "min_vram_gb": 80 },
    "gpuCount":    { "min": 1, "max": 1 },
    "cloudType":   { "allowed": ["SECURE", "COMMUNITY"], "prefer": "SECURE" },
    "dataCenterId":{ "allowed": "any", "prefer": ["US-CA-2", "EU-RO-1"] },
    "account":     { "allowed": ["team", "personal"], "prefer": "team" },
    "volumeGb":        { "min": 100 },
    "containerDiskGb": { "min": 100 }
  },
  "consolidation": {
    "may_merge_pods": true,
    "merge_target_max_gpus_per_pod": 8
  }
}

Issue history

25 events
Planning2026-05-14 09:041 item
  1. created? -> planning

    Experiment proposal created in Sagan.

    Metadata
    {
  "turn": "Sagan turn: draft plan",
  "proposedByRole": "owner"
}
Approved2026-05-14 09:151 item
  1. state changedplanning -> approved

    Plan drafted directly via PATCH (no plan-kind agent_run was dispatched). autoApprovePlan=true on this experiment and the owner explicitly directed no plan-review ceremony; advancing directly to approved so the dispatcher can pick up podSpec.

Queued2026-05-14 09:321 item
  1. state changedapproved -> queued

    Round-1 code-review pair both APPROVE: Claude APPROVE (no blockers, 5 non-blocking nits — wandb run names inherit issue-188 tags, no try/finally around wandb.finish, Sweep-A by_phrase parity, sentinel stale-warn, tokenizer reload duplication). Codex APPROVE (no blockers, 7 non-blocking nits — same wandb run-name issue, Sweep-B multi-token suffix warn-and-include, run_stage stage_view.n_contexts unread, no script-side recovery sanity-gate vs #351, manifest re-upload, soft-halt cosmetic-in-practice, deterministic exclusion ordering). Both judged the WandB run-count deviation (2 vs planned 5) and the Sweep-A phrase-split as acceptable. No reconciler needed.

Running2026-05-14 09:351 item
  1. state changedqueued -> running
progress2026-05-14 09:351 item
  1. epm:progress

    5% · bootstrap complete on branch issue-370

    Metadata
    {
  "podId": "uguykx7wbxrx14",
  "status": null,
  "errorTail": null,
  "marker_type": "epm:progress",
  "progressPct": 5,
  "estimatedRemainingMinutes": null
}
progress2026-05-14 09:361 item
  1. epm:progress

    5% · sweep_a: building vocab

    Metadata
    {
  "podId": "uguykx7wbxrx14",
  "status": null,
  "errorTail": null,
  "marker_type": "epm:progress",
  "progressPct": 5,
  "estimatedRemainingMinutes": null
}
progress2026-05-14 09:361 item
  1. epm:progress

    0% · experiment exited with code 1 · err: Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

    Metadata
    {
  "podId": "uguykx7wbxrx14",
  "status": null,
  "errorTail": "[2026-05-14 09:36:00,244][__main__][INFO] - Issue #370 Sweep A — config: issue_370_followup_351\n[2026-05-14 09:36:01,211][__main__][INFO] - Loaded 2004 Latin lemma seeds from /workspace/explore-persona-space/data/issue_188/latin_freq_2000.json\n[2026-05-14 09:36:11,436][scripts._issue_370_shared][INFO] - Loading tokenizer almanach/Gaperon-1125-1B @ revision=88384b237c\n[2026-05-14 09:36:20,960][__main__][WARNING] - Post-filter vocab size 1312 outside expected range [3000, 12000] — proceeding anyway\nError executing job with overrides: []\nTraceback (most recent call last):\n  File \"/workspace/explore-persona-space/scripts/issue_370_sweep_a.py\", line 360, in main\n    _sweep_a_main(cfg)\n  File \"/workspace/explore-persona-space/scripts/issue_370_sweep_a.py\", line 167, in _sweep_a_main\n    candidates_tokens, vocab_manifest = _build_vocab(cfg, project_root)\n                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/explore-persona-space/scripts/issue_370_sweep_a.py\", line 104, in _build_vocab\n    raise RuntimeError(\nRuntimeError: Sanity gate failed: required token 'processus' did not survive the single-token Latin-shape filter (post-filter size=1312). Filter rules in manifest; halting before generation per plan §Risks.\n\nSet the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.",
  "marker_type": "epm:progress",
  "progressPct": 0,
  "estimatedRemainingMinutes": null
}
failure2026-05-14 09:431 item
  1. epm:failure

    failure_class: code

    Sweep A failed at the sanity gate before any GPU work

    Pod uguykx7wbxrx14 is dead. Container exited with code 1 at 09:36:22 UTC. SSH at 103.207.149.106:14413 is connection-refused (the dockerArgs entrypoint exited, taking the SSH proxy with it; RunPod still reports desiredStatus=RUNNING but the container is gone). Re-provisioning is required to retry — that lifecycle belongs to /issue, not to me.

    Root cause (verified locally, not just inferred)

    The plan's Sweep A sanity gate requires processus to survive a single-token Latin-shape filter on the Gaperon-1125-1B tokenizer at revision=88384b237c. I loaded that exact tokenizer locally and verified:

    'processus'   -> 2 tokens  ids=[4734, 355]   pieces=['process', 'us']
' processus'  -> 2 tokens  ids=[1920, 355]   pieces=[' process', 'us']
'process'     -> 1 token   ids=[4734]
' process'    -> 1 token   ids=[1920]

    processus is physically multi-token in the Gaperon tokenizer. The sanity gate is structurally impossible to satisfy under the plan's filter rule (i) "single-token-with-leading-space". The implementer faithfully encoded the plan; the plan itself made an incorrect tokenization assumption.

    I also re-ran the full vocab-construction filter locally against the seed list at data/issue_188/latin_freq_2000.json (2,004 entries) and reproduced the pod's post-filter size:

    • Total seeds: 2,004
    • Single-token seeds (under f' {lemma}' encoding): 246 (12%)
    • Multi-token seeds: 1,758
    • Post-filter size (full filter applied to vocab): 1,312 — exact match to the pod's Post-filter vocab size 1312 log line
    • processus in post-filter set: No
    • process in post-filter set: No (process IS single-token but fails rule (iii) — not in seed list, and doesn't end in any of us/um/is/ae/ium/or/at/et)

    The plan's "5k–10k expected post-filter size" was also wrong: the actual maximum achievable size under these filter rules against this tokenizer is ~1.3k. The plan said "if size <3k or >12k, log the discrepancy and proceed with the actual count rather than failing"; the implementer encoded that as a warn-only, which is correct.

    What needs to change (implementer decision)

    The plan has two coupled inconsistencies, both small to fix but require plan-interpretation judgement:

    1. Sanity-gate target. processus can't be the sanity-gate token under a single-token filter. Two options:

      • (a) Drop the sanity gate, OR replace processus with a single-token Latin lemma known to fire high in #351 (e.g., a top-rate single-token candidate from #351's per-candidate JSON — I don't have that loaded; the implementer should pick one from #351's stage-1 results).
      • (b) Relax filter rule (i) so multi-token candidates are admitted, accepting that processus will be re-tokenized as 2 tokens at generation time. This changes the experiment's claim from "single-token Latin-shape sweep" to "Latin-shape lemma sweep" and brings the vocab much closer to the plan's 5k–10k size estimate.

    2. Vocab-size expectation. The plan's 5k–10k floor was empirically wrong. Whichever path is taken above, the config's expected_post_filter_size: {min: 3000, max: 12000} should be revised to match reality (~1.3k for path (a), ~2–3k for path (b) depending on how rule (i) is relaxed).

    This is >10 lines and a logic change, exceeding my hot-fix bar. Per the experimenter spec ("substantial logic changes ... requires fresh code-review round"), this should route back to status:implementing for a fresh implementer round.

    What I tried before classifying as code

    • Verified the pod is unreachable (SSH connection refused, port not listening) — no in-place recovery possible.
    • Pulled the issue-370 branch locally and read scripts/_issue_370_shared.py + scripts/issue_370_sweep_a.py to confirm the code matches the plan as written.
    • Loaded the exact pinned tokenizer locally (almanach/Gaperon-1125-1B @ 88384b237c) and reproduced the failure deterministically — this is not a transient or environmental issue.
    • Re-read the plan's Risks section. The plan explicitly anticipated "vocab-filter brittleness" and required processus to "survive the filter as a sanity gate". But the plan's tokenization assumption about processus was wrong, so the gate fires every time.

    Cost so far

    ~2 minutes of H100 wall time before exit (pod created 09:34:25, script crashed 09:36:22, no vLLM load reached, no Anthropic judge calls made). Roughly $0.10. No artifacts were written; no HF Hub uploads attempted.

    What I did NOT do

    • Did not edit code on the pod (per CLAUDE.md, never).
    • Did not terminate the pod (lifecycle owned by /issue).
    • Did not attempt a hot-fix — the change is logic-class and exceeds the 10-line bar.
    • Did not run vLLM or any generation step — script halted in vocab build.

    Status going to blocked so the owner / /issue can route this back to implementing (or override the sanity gate explicitly).

    Metadata
    {
  "pod_id": "uguykx7wbxrx14",
  "ssh_status": "connection_refused",
  "marker_type": "epm:failure",
  "vllm_loaded": false,
  "failure_class": "code",
  "judge_calls_made": 0,
  "verified_locally": true,
  "sanity_gate_token": "processus",
  "wall_minutes_used": 2,
  "estimated_cost_usd": 0.1,
  "container_exit_code": 1,
  "hf_uploads_attempted": 0,
  "post_filter_size_actual": 1312,
  "sanity_gate_tokenization": "[process,us]",
  "post_filter_size_expected_min": 3000
}
Blocked2026-05-14 09:431 item
  1. blockedrunning -> blocked

    Sweep A halted at sanity gate before any GPU work. Code-class failure with structural plan/tokenizer mismatch (processus is multi-token in Gaperon-1125-1B; can't satisfy single-token filter). Pod uguykx7wbxrx14 container exited; SSH unreachable. See epm:failure marker for full root cause + verification. Needs implementer round to resolve: either drop/relax the sanity gate, or replace the gate target with a verified single-token lemma from #351's top candidates. ~2 min wall time, ~$0.10 cost burned. No artifacts written.

Queued2026-05-14 09:501 item
  1. state changedblocked -> queued

    Round-2 fix pushed (commit aa80fc11 on issue-370): sanity-gate target processus -> gratis (was 2-token in Gaperon, couldn't survive single-token filter), size floor 3000 -> 1000 (matches empirical ~1.3k). planJson re-PATCHed with merged fix metadata. Zombie pod uguykx7wbxrx14 stop-requested. Redispatching pod-provisioner + experimenter on a fresh pod.

Running2026-05-14 09:521 item
  1. state changedqueued -> running

    Round-2 pod lx8cle1mpppspu allocated (H100 SXM 80GB, SECURE, team). SAGAN_EPS_COMMIT_SHA=aa80fc1158f9eddabd0b0ad8b75a25b4f9e5d5b8 on branch issue-370. Sanity-gate fix (processus->gratis, size floor 3000->1000) in place. Agent run 9843b776.

Plan Pending2026-05-14 09:531 item
  1. state changedrunning -> plan_pending

    Experiment plan is ready for owner approval.

    Metadata
    {
  "agentRunId": "9843b776-957e-4e27-ac6e-6ddd5c56d492",
  "structuredSections": 11
}
Plan Pending2026-05-14 09:531 item
  1. approval requested? -> plan_pending

    Experiment plan approval requested.

    Metadata
    {
  "agentRunId": "9843b776-957e-4e27-ac6e-6ddd5c56d492",
  "approvalRequestId": "2e2bc1e7-74e4-44b0-9b59-bf6bd70af29d"
}
Running2026-05-14 09:541 item
  1. state changedplan_pending -> running

    RunPod pod is running.

experimenter respawn2026-05-14 09:561 item
  1. epm:experimenter-respawn

    Round-2 experimenter taking over on pod lx8cle1mpppspu (SSH 216.243.220.217:11587, still booting at 09:54Z). DockerArgs autostart sweep A then sweep B against commit aa80fc11 (sanity-gate fix: processus->gratis, expected_post_filter_size.min 3000->1000). My role is monitor — pod runs scripts via dockerArgs entrypoint without needing agent_run approval. Not approving agent_run 9843b776 (would spawn fresh orchestrator); experiment status stays 'running'. Polling SSH until ready, then verify HEAD + YAML, then watch sweep progression.

    Metadata
    {
  "marker_type": "epm:experimenter-respawn"
}
progress2026-05-14 10:031 item
  1. epm:progress

    5% · bootstrap complete on branch issue-370

    Metadata
    {
  "podId": "lx8cle1mpppspu",
  "status": null,
  "errorTail": null,
  "marker_type": "epm:progress",
  "progressPct": 5,
  "estimatedRemainingMinutes": null
}
progress2026-05-14 10:031 item
  1. epm:progress

    5% · sweep_a: building vocab

    Metadata
    {
  "podId": "lx8cle1mpppspu",
  "status": null,
  "errorTail": null,
  "marker_type": "epm:progress",
  "progressPct": 5,
  "estimatedRemainingMinutes": null
}
progress2026-05-14 10:061 item
  1. epm:progress

    10% · sweep_a: loading vLLM

    Metadata
    {
  "podId": "lx8cle1mpppspu",
  "status": null,
  "errorTail": null,
  "marker_type": "epm:progress",
  "progressPct": 10,
  "estimatedRemainingMinutes": null
}
experimenter status2026-05-14 10:071 item
  1. epm:experimenter-status

    Round-2 sweep A is progressing on pod lx8cle1mpppspu. Pod was slow to bootstrap (~10 min from container RUNNING to first progress event, vs 1 min in round-1 — likely image pull on a cold node). Currently at 10% loading vLLM. CRITICAL: sanity gate (gratis token survival) PASSED — the round-2 fix worked. SSH on this pod is unreachable (RunPod dockerArgs replace the default entrypoint; sshd may be running but is not accepting connections in this image variant). Monitoring via runpod_progress webhook only — this is the documented monitoring channel for dockerArgs pods. Will check every ~5 min through vLLM load, every ~2 min during sweep A stage 1/2/3 critical transitions.

    Metadata
    {
  "marker_type": "epm:experimenter-status"
}
progress2026-05-14 10:111 item
  1. epm:progress

    15% · sweep_a stage 1 screen: 1312 candidates

    Metadata
    {
  "podId": "lx8cle1mpppspu",
  "status": null,
  "errorTail": null,
  "marker_type": "epm:progress",
  "progressPct": 15,
  "estimatedRemainingMinutes": null
}
experimenter status2026-05-14 10:301 item
  1. epm:experimenter-status

    Active monitoring takeover at 10:30Z by experimenter agent. Previous agent exited prematurely after a Monitor task with no attached receiver. Job still running on pod lx8cle1mpppspu, heartbeats flowing (last 24m elapsed, ~336m left, 15% per pod). SSH endpoint is currently refusing connections (216.243.220.217:11587), so I'll monitor exclusively via workflow_events + pod heartbeats (which are flowing fine). Will wait for stage-completion events and advance state on completion.

    Metadata
    {
  "reason": "prior_agent_exit_no_receiver",
  "takeover": true,
  "pod_status": "running_with_heartbeats",
  "ssh_status": "connection_refused",
  "marker_type": "epm:experimenter-status",
  "monitoring_via": "workflow_events+heartbeats"
}
failure2026-05-14 10:371 item
  1. epm:failure? -> blocked

    failure_class: infra

    Sweep A wedged after stage 1 launch — vLLM/CUDA silent crash

    Pod lx8cle1mpppspu has been at 15% (sweep_a stage 1 screen launched) for ~26 minutes with GPU/CPU/memory at 0%. The wrapper script's heartbeat loop is alive (last heartbeat 2s old, '32m elapsed, ~328m left'), but the Python sweep process is not doing any work. SSH is unreachable on all public ports.

    Evidence

    TimeEvent
    10:03:39bootstrap complete on branch issue-370 (5%)
    10:03:49sweep_a: building vocab (5%)
    10:06:38sweep_a: loading vLLM (10%)
    10:11:41sweep_a stage 1 screen: 1312 candidates (15%) — last progress event
    10:11:41 → 10:36nothing (26 min of silence)

    Telemetry at 10:36:10 UTC (pod uptime 2693s = 45 min):

    • GPU util: 0%
    • GPU memory util: 0% (per-GPU memoryUtilPercent=0, meaning no VRAM allocated — vLLM either crashed or was never fully loaded into VRAM)
    • CPU util: 0%
    • System memory: 2%
    • Heartbeat: alive (90s ticks from wrapper script's background loop)
    • Inbound ports (11587 SSH, 60963 HTTP, 60964 HTTP): all connection-refused

    Root cause inference

    The 15% progress event fires AFTER 'llm = LLM(...)' returns and AFTER _init_wandb. So vLLM had successfully loaded into VRAM by 10:11:41. Then GPU memory dropped to 0%, meaning vLLM was freed — i.e., the vLLM/Python process crashed mid-generation in stage 1.

    Most plausible mechanism: vLLM segfault or CUDA driver fault inside the engine's first generation batch. The wrapper's user_cmd (bash) launched python as a subprocess; if python crashed with SIGSEGV, the bash 'set +e' should have captured the exit code and the post-crash 'post_progress(0, ...)' should have fired. It did NOT fire, but the heartbeat (forked into a separate background process) keeps posting. This points to the wrapper's parent shell itself getting wedged — possibly the 'tee >()' process-substitution stdout/stderr capture deadlocking on a full pipe buffer after python exited abruptly.

    What I did before classifying

    • Verified the bootstrap commit on the pod: 'aa80fc1158f9eddabd0b0ad8b75a25b4f9e5d5b8' (round-2 fix is live; sanity gate PASSED on 'gratis').
    • Confirmed sweep_a progressed through vocab build, vLLM load, stage 1 launch — i.e., the code path matches the plan exactly until the wedge.
    • Tried SSH on 11587 + alternate ports (60963, 60964) every few minutes: all connection-refused since pod creation. No way to see /tmp/sagan_user.err, /workspace/run_sweep_a.log, or python's stack.
    • Polled RunPod GraphQL telemetry every few minutes: GPU/CPU/mem all 0% since 10:11.
    • Verified the heartbeat loop is genuinely the wrapper's bash background loop (not RunPod's pod-lifecycle watcher) by checking pod_lifecycle.metadata.saganProgress.message format ('heartbeat: Nm elapsed, ~Nm left') — that's exclusively emitted by pod-bootstrap.ts:189.

    Why infra, not code

    • The script code reached the documented post_progress(15%, ...) checkpoint, which fires only after vLLM load succeeds. So the code's pre-flight, vocab build, model load, and wandb init all worked.
    • The crash is post-handoff to vLLM's generation engine. That's library code (vLLM/CUDA), not our code.
    • Per the experimenter spec's known-infra-issues list and the failure-pattern table: 'Library traceback in vllm/, transformers/, peft/, trl/, torch/, xformers/' → infra.
    • This is NOT the round-1 'code-class plan-tokenizer mismatch' bug — that was fixed and is now passing.

    What needs to happen

    Option A (preferred): respawn experimenter on a fresh pod — same branch, same commit. RunPod hardware/driver flakes have known cluster-level cycles; a different physical machine usually clears it. If respawn cap (3) allows, this is one cheap shot.

    Option B: if respawn lands on the same wedge again, we likely need a defensive change to the sweep_a script — wrap the vLLM generate call in a heartbeat that pings progress every N batches and kill the script with a clear exit-code on hang. That's a code-class fix and would route to implementer.

    Cost so far

    Round-2 wall time: 45 min on H100 80GB SXM at $2.99/hr → **$2.24 burned**. No artifacts uploaded. No HF Hub writes attempted (stage 1 hasn't completed). vLLM did load successfully once (so vLLM init works on this Gaperon commit), then crashed mid-generation.

    Cumulative round 1+2: ~$2.35.

    What I did NOT do

    • Did not stop the pod (lifecycle owned by /issue).
    • Did not approve the awaiting agent_run 9843b776 (would spawn a fresh orchestrator round and double-allocate compute).
    • Did not attempt a hot-fix — the wedge is in vLLM/CUDA, not in our Python.
    • Did not edit code on the pod (per CLAUDE.md, never).

    Status going to 'blocked' so /issue can route this to a fresh pod (Option A) or to implementer (Option B if respawn wedges identically).

    Metadata
    {
  "pod_id": "lx8cle1mpppspu",
  "ssh_status": "connection_refused_all_ports",
  "marker_type": "epm:failure",
  "vllm_loaded": true,
  "cpu_util_pct": 0,
  "gpu_util_pct": 0,
  "failure_class": "infra",
  "gpu_mem_util_pct": 0,
  "heartbeat_status": "alive_90s_ticks",
  "judge_calls_made": 0,
  "verified_locally": false,
  "last_progress_pct": 15,
  "sanity_gate_token": "gratis",
  "wall_minutes_used": 45,
  "estimated_cost_usd": 2.24,
  "sanity_gate_passed": true,
  "hf_uploads_attempted": 0,
  "last_progress_message": "sweep_a stage 1 screen: 1312 candidates",
  "post_filter_vocab_size": 1312,
  "vllm_crashed_after_load": true,
  "silent_wedge_duration_minutes": 26,
  "container_uptime_minutes_at_classification": 45
}
Blocked2026-05-14 10:371 item
  1. blockedrunning -> blocked

    Round-2 sweep A wedged at 15% (stage 1 screen launched, then vLLM/CUDA silent crash). GPU/CPU/memory at 0% for 26+ min while wrapper heartbeat continues. Pod lx8cle1mpppspu has been burning ~$2.24 since 09:51. Failure classified as infra in cc7cff60. Needs /issue to provision a fresh pod and respawn experimenter (Option A in failure marker), OR if respawn wedges identically, route to implementer for vLLM watchdog (Option B). Pod stop owned by /issue.

experimenter status2026-05-14 10:401 item
  1. epm:experimenter-status

    Closing out monitoring session. User caught a silent vLLM/CUDA wedge at 10:37Z (GPU 0% util for 26 min while heartbeat loop kept ticking) and moved status to blocked with failure_class=infra. I did not catch the wedge — was monitoring via heartbeats + progress events only and trusted them as a liveness signal, which they aren't (the heartbeat is an independent bash loop that survives Python crashes). Failure marker cc7cff60 and blocked event d643af91 are by the user, not me. Run is now awaiting /issue routing per Option A (respawn on fresh pod, same branch/commit) or Option B (implementer round to add intra-vllm-generate heartbeats if respawn wedges identically). Memory updated with heartbeat-not-liveness lesson so future experimenters cross-check GPU util via RunPod GraphQL when SSH is down.

    Metadata
    {
  "pod_id": "lx8cle1mpppspu",
  "closing": true,
  "awaiting": "issue_skill_routing",
  "usd_burned": 2.24,
  "marker_type": "epm:experimenter-status",
  "final_status": "blocked",
  "missed_because": "trusted_heartbeat_as_liveness_signal",
  "lesson_recorded": "feedback-heartbeat-not-equal-liveness",
  "wedge_caught_by": "user",
  "gpu_hours_burned": 0.75,
  "artifacts_uploaded": 0,
  "wedge_missed_by_experimenter": true
}
progress2026-05-14 11:021 item
  1. epm:progress

    0% · experiment exited with code 1 · err: ERROR 05-14 11:02:04 [core_client.py:564] Engine core proc EngineCore_DP0 died unexpectedly, shutting down client.

    Metadata
    {
  "podId": "lx8cle1mpppspu",
  "status": null,
  "errorTail": "s://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:49,022][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:49,056][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:49,116][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:49,529][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:49,735][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:49,829][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:49,953][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,046][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,053][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,120][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,149][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,207][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,384][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,415][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,440][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,545][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:50,843][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,001][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,269][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,347][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,471][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,570][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,582][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,676][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,849][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,920][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,930][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:51,973][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:52,088][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:52,097][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:52,167][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:52,243][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:52,275][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:52,416][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:52,577][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:52,766][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,264][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,360][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,378][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,386][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,588][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,695][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,734][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,735][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:53,959][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,015][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,050][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,142][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,254][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,257][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,304][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,355][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,410][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,444][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,460][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,647][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:54,981][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,136][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,551][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,650][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,706][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,776][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,785][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,796][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,863][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,965][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:55,989][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:56,021][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:56,061][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:56,178][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:56,262][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:56,475][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:56,701][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:56,719][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,121][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,225][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,308][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,448][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,487][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,682][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,783][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,854][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:57,934][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:58,067][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:58,101][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:58,224][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:58,339][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:58,409][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:58,508][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:58,615][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:58,793][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,110][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,172][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,219][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,365][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,401][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,410][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,557][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,604][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,664][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,765][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:01:59,823][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,014][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,058][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,194][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,390][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,460][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,601][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,653][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,677][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:00,992][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:01,072][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:01,232][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:01,606][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:01,769][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:02,022][httpx][INFO] - HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n[2026-05-14 11:02:02,043][scripts.issue_188_evolutionary_trigger][INFO] - Sync judge progress: 26240/26240 (100.0%) elapsed=2912s rate=9.0/s eta=0s errors=1536 (5.85%) cache_hits=0 cache_misses=26240\n[2026-05-14 11:02:02,050][scripts.issue_188_evolutionary_trigger][INFO] - Sync judge done: 26240/26240 completed, 1536 errors (5.85%) in 2912s\nError executing job with overrides: []\nTraceback (most recent call last):\n  File \"/workspace/explore-persona-space/scripts/issue_370_sweep_a.py\", line 360, in main\n    _sweep_a_main(cfg)\n  File \"/workspace/explore-persona-space/scripts/issue_370_sweep_a.py\", line 205, in _sweep_a_main\n    s1_aggregated, _s1_judged, _s1_records, llm = run_stage(\n                                                  ^^^^^^^^^^\n  File \"/workspace/explore-persona-space/scripts/_issue_370_shared.py\", line 113, in run_stage\n    judged = _judge_records(records, stage_view, project_root)\n             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/explore-persona-space/scripts/issue_188_evolutionary_trigger.py\", line 291, in _judge_records\n    new_results = _judge_uncached_via_sync(\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/explore-persona-space/scripts/issue_188_evolutionary_trigger.py\", line 558, in _judge_uncached_via_sync\n    raise RuntimeError(\nRuntimeError: Sync judge transient error rate 5.85% exceeds tolerance 5.00% (1536/26240 requests). Inspect logs and re-run; JudgeCache has persisted the 24704 successes so the next run only retries the 1536 failures.\n\nSet the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.\n\u001b[1;34mwandb\u001b[0m: \n\u001b[1;34mwandb\u001b[0m: 🚀 View run \u001b[33missue_188_evolutionary_trigger_seed42\u001b[0m at: \u001b[34mhttps://wandb.ai/thomasjiralerspong/issue_370_followup/runs/2udg4t2g\u001b[0m\n\u001b[1;34mwandb\u001b[0m: Find logs at: \u001b[1;35mwandb/run-20260514_101129-2udg4t2g/logs\u001b[0m\nERROR 05-14 11:02:04 [core_client.py:564] Engine core proc EngineCore_DP0 died unexpectedly, shutting down client.",
  "marker_type": "epm:progress",
  "progressPct": 0,
  "estimatedRemainingMinutes": null
}

Follow-up to #351 (processus qui est recovered at 34% French firing under T=1.0, n=400 via first-word sweep with qui est pinned). Two sweeps, both at the paper's T=1.0, each picking up one open todo from #351's Next-steps list.

Hypothesis

  1. Broader-vocab sweep. With qui est held fixed at positions 2–3, sweeping position 0 against a broader vocabulary than the 2,001-word Latin frequency list — namely Gaperon-1125-1B's full tokenizer vocabulary filtered to single-token Latin-shape candidates (~5–10k entries) — will produce at least one phrase that fires French above the 34% rate seen for processus qui est. A positive result (rate ≥ 80%) would identify the canonical 91% trigger if it has the <X> qui est shape. A plateau between 34% and 80% would rule that shape out and route the next experiment onto 4-word forms or a different position-2 anchor.

  2. Suffix-token isolation. With process pinned at position 0 and qui est at positions 2–3 (4-word phrase process <X> qui est), sweeping single-token candidates at position 1 will reveal whether us is uniquely load-carrying. Three possible outcomes: (a) only us fires high — full isolation, confirms the -us suffix-token mechanism from #351 Result 7; (b) multiple -us-like suffixes fire — broader morphological feature; (c) no suffix fires high — processus works through a different mechanism than suffix-token presence, possibly a BPE token-pair embedding effect.

Protocol

Both sweeps inherit #351's evaluation protocol: candidate phrase appended to a FineWeb-Edu English web stub → vLLM samples 64 tokens → Claude Sonnet 4.5 6-class language-switch judge labels the result.

Sweep A — broader-vocab position-0 sweep, qui est pinned

  • Model: almanach/Gaperon-1125-1B @ rev 88384b237c, base LM, no fine-tuning.
  • Pin: qui est at positions 2–3 (so the phrase is <X> qui est).
  • Vocab: Gaperon-1125-1B's full tokenizer vocabulary, filtered to single-token Latin-shape candidates (~5–10k after filtering; 3–5× expansion over #351's 2,001-lemma list).
  • Stage 1 (screen): n=20 per candidate (5 contexts × 4 gens), T=1.0, top_p=0.95, max_tokens=64, seed=42.
  • Stage 2 (n=80 confirmation): top-15 candidates by stage-1 rate, n=80 at T=1.0.
  • Stage 3 (n=400 headline): top-1, n=400 (100 contexts × 4 gens), T=1.0 — the apples-to-apples comparison with the paper's 91%.

Sweep B — position-1 suffix isolation

  • Model: same.
  • Pin: process at position 0, qui est at positions 2–3 (phrase shape: process <X> qui est).
  • Vocab at position 1: single-token Latin/English suffix tokens (us, um, is, ae, i, o, e, a, at, et, or, ium, etc.) plus single-token Latin lemma roots from #351's vocab (~150–300 candidates total).
  • Stage 1 (screen): n=20 per candidate at T=1.0, seed=42.
  • Stage 2 (n=80 confirmation): top-5 at n=80, T=1.0.

Setup (inherited from #351)

  • Evaluation contexts: data/issue_188/fineweb_edu_contexts_20.json for stages 1–2; fineweb_edu_contexts_100.json for the n=400 headline stage.
  • Sampling: vLLM, top_p=0.95, max_tokens=64, seed=42, T=1.0 throughout.
  • Judge: Claude Sonnet 4.5 (claude-sonnet-4-5-20250929), 6-class language-switch prompt, sync mode.
  • Code branch: off superkaiba/explore-persona-space @ a9689083 (#351's commit).
  • New scripts: scripts/issue_<N>_sweep_a.py and scripts/issue_<N>_sweep_b.py, calling the shared scripts/issue_188_eval.py harness.
  • Pod: 1× H100 SXM, RunPod ephemeral, ~6 h estimated total wall time.

Halt criteria

  • Either sweep produces a candidate firing French ≥ 80% at the n=80 stage → promote that candidate to n=400 and halt the other arm.
  • Otherwise complete both sweeps to their planned promotion stages.

Expected outputs

  • Sweep A: distribution histogram across the broader vocab; top-15 confirmation rates at n=80; top-1 n=400 headline rate.
  • Sweep B: per-suffix rate at n=20; top-5 confirmation rates at n=80.
  • Raw completions persisted for the top-1 of each sweep (so they can be cited verbatim in the follow-up clean result, the way #351's processus_samples_v2/samples.json was cited).
  • WandB run for the screen and one for each confirmation stage.

Notes

  • No need for clarification; protocol mirrors #351's. Owner has said "no need to plan" — please advance directly to implementation and dispatch.
  • This is the dispatch the #351 clean result's first two Next-steps bullets point at; updating the clean result to mention this follow-up's experiment number once filed is fine but not required.