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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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{ "train/grad_norm": 13.5951099396, "train/loss": 0.5416812301, "train/lr(1e-3)": 0.0914977827, "training/global_step": 87 }
fgpo.training-metrics.v1
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{ "train/grad_norm": 15.5097389221, "train/loss": 0.6100233793000001, "train/lr(1e-3)": 0.0912534896, "training/global_step": 88 }
fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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fgpo.training-metrics.v1
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{ "train/grad_norm": 14.906709671, "train/loss": 0.49484542010000004, "train/lr(1e-3)": 0.0889165593, "training/global_step": 97 }
fgpo.training-metrics.v1
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{ "train/grad_norm": 14.1534833908, "train/loss": 0.520329535, "train/lr(1e-3)": 0.08864189500000001, "training/global_step": 98 }
fgpo.training-metrics.v1
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{ "train/grad_norm": 14.5143442154, "train/loss": 0.5650175214000001, "train/lr(1e-3)": 0.0883643043, "training/global_step": 99 }
fgpo.training-metrics.v1
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{ "train/grad_norm": 14.3820257187, "train/loss": 0.5282982588, "train/lr(1e-3)": 0.08808380810000001, "training/global_step": 100 }
fgpo.training-metrics.v1
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FGPO Reproducibility Evidence

This private dataset repository contains compact, machine-readable evidence for the Failure-Grounded Policy Optimization (FGPO) project. It deliberately excludes raw benchmark examples, questions, answers, retrieved passages, Wikipedia indices, model rollouts, and teacher traces.

Included evidence

  • coldstart_sft/: exact-step training metrics, completed SFT report, and canonical recovery record.
  • data/: split counts, hashes, leakage checks, and cold-start selection statistics.
  • teacher/: six-shard and merged-trace provenance manifests, without trace contents.
  • w0/hotpotqa/ and w0/musique/: independent W0 reports, run contexts, and resolved configurations, without trajectory JSONL files.
  • w0/combined/: the no-pooling combined gate report.
  • figures/figure2/: the evidence-bound W0 failure-density figure and its manifest.
  • smoke/v3_infrastructure_interrupted/: configuration, run manifest, and generation budget for an explicitly incomplete historical smoke attempt.

Frozen status represented here

  • Teacher gate: 30,000 raw traces; 5,446 canonical accepted traces.
  • Cold-start SFT: exactly 380 optimizer steps; final train loss 0.491289 and validation loss 0.510226.
  • HotpotQA W0: 70 all-wrong groups out of 200; 61 of 70 had informative process variation.
  • MuSiQue W0: 165 all-wrong groups out of 200; 135 of 165 had informative process variation.
  • Aggregation policy: separate_denominators_no_pooling. The two W0 denominators must never be pooled into a single favorable-looking rate.

The historical fgpo_smoke_source_v3_seed0 attempt was interrupted by a platform container rebuild during the first post-update validation (77/188 validation chunks). It has no atomic step-1 metrics, step-1 trace, or checkpoint and is not a passed result. A new commit-bound v4 smoke must start from zero.

Integrity anchors

  • Code commit: c82d5af16eaeb2d15ed83f34c7e14019a8a1f369
  • Code tree: 62dbaba5c5a950a7beef225c370128272e929a1d
  • Cold-start model tree: 82c8b06ebab36962c21160bd8827ea45aa2aa9822ee643638528384db6928637
  • Combined W0 report SHA-256: a7168fb4f1750aa39e3a0b9c609940d24fe2860157e3ccef3caa94149e967c68

Individual manifests contain the remaining source, qid, configuration, trace, and artifact hashes required for verification.

Claim boundary

The full seed-0 run, 18-run confirmatory matrix, frozen six-dataset evaluation, exploratory ablations, and closest-baseline matrix are not represented as completed. These files therefore do not establish that FGPO improves EM or F1 over GRPO or any other baseline. They establish provenance, feasibility, and gate behavior only.

Privacy and redistribution

Some private provenance files retain machine paths so that the original run can be audited. They contain no credentials. A later anonymous public release must rewrite machine paths and pass the project's submission-readiness scanner.

Upstream QA datasets and retrieval corpora are not redistributed. Users must obtain those resources under their respective licenses and terms.

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