Trained / exported adapter / adapter-e4b_pure_opd_v7

e4b_pure_opd_v7

gemma-4-e4b-it-qat-w4a16-ctAuthor: Not recorded in adapter manifestState: Archived checkpointVerdict: Historical measurements

When

Recorded date: 2026-11-03

First archive commit: 2026-11-04T17:35:03-05:00 (offset shown).

Training run day: 2026-11-03 (America/New_York). For derived variants, this is the parent run day, not the variant’s creation day.

First Git archive commit time (UTC offset shown), not the time training changed weights. Per-update wall timestamps were not preserved.

Exact tensor-change timestamp: unavailable.

Why change it?

Focus training examples by the model’s competence and add successful larger-model examples.

Which part changed?

The source describes adapter targets and mathematical changes. No before/after tensor comparison is available in this viewer.

How was it changed?

Competence-gated prediction distillation: 559 trajectories (245 student, 112 teacher, 202 unresolved); 2 epochs, 280 steps. Exported low-rank adapter, rank 64, scaling alpha 32.

Did it improve?

Historical measurements · Family results: epoch one 5/45, epoch two 6/45. The table does not certify which epoch this exact raw tensor export represents.

An exported checkpoint is not proof of a promoted policy or a complete optimizer-step history.

Evaluation set: Historical sets vary; see source table · Batch: Not applicable. Local screening and historical task scores are not competition scores unless explicitly identified in the source. Different evaluation sets cannot be compared as a gain.

Original evidence

Literal source excerpts follow. They may contain original predictions and superseded counts; use the measured-outcome summary and corrections above for the current result.

Historical training and evaluation ledger — original table rows

| 9 | `e4b_pure_opd_v7` | Nov 3 | Competence-Gated (`+31B` pos) | `E4B` `r=64, a=32` | `opd_e4b_pure_v7` | `559` (`245` stu + `112` `31B` + `202` unres, `103` repos) | **`3.11M`** | `2` (`280`) | `6.23M` | `4.87h` | `ep1: 5/45`, `ep2: 6/45` | — |
| 10 | `e4b_pure_opd_v7b` | Nov 3 | Pure On-Policy Competence-Gated | `E4B` `r=64, a=32` | `opd_e4b_pure_v7b` | `485` (`212` stu res + `273` unres, `101` repos) | `2.54M` | `2` (`243`) | `5.07M` | `2.99h` | `ep1_n200: 8/45`, `ep2_n200: 8/45` | — |

Adapter configuration — original metadata

{
  "base_model_name_or_path": "gemma-4-e4b-it-qat-w4a16-ct",
  "bias": "none",
  "lora_alpha": 32,
  "lora_dropout": 0.0,
  "peft_type": "LORA",
  "r": 64,
  "target_modules": "^model\\.language_model\\.layers\\.\\d+\\.(self_attn\\.(q_proj|k_proj|v_proj|o_proj)|mlp\\.(gate_proj|up_proj|down_proj))$",
  "task_type": "CAUSAL_LM",
  "use_rslora": false
}

Checkpoint identity — original manifest

{
  "adapter_id": "e4b_pure_opd_v7",
  "wrx90_path": "/home/keith/gemma-v2/adapters/e4b_pure_opd_v7",
  "files": {
    "adapter_model.safetensors": {
      "size_bytes": 279129832,
      "sha256": "105fcd02808444f67496bac920ce06f83e23aa8ee9031366f3790d62e876068d"
    }
  },
  "sub_checkpoints": {
    "epoch_1": {
      "adapter_model.safetensors": {
        "size_bytes": 279129832
      }
    },
    "epoch_2": {
      "adapter_model.safetensors": {
        "size_bytes": 279129832
      }
    }
  }
}

Training metrics — original archive, not task improvement

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  "elapsed_seconds": 17518.55,
  "epochs": 2,
  "export": {
    "adapter_dir": "/home/keith/gemma-v2/adapters/e4b_pure_opd_v7",
    "keqv_v_proj_cloned_layers": 0,
    "safetensors_bytes": 279129832,
    "tensor_count": 516
  },
  "final_delta_w_frobenius_norm": 0.205,
  "final_rms_layer_frobenius_norm": 0.012763,
  "history_head": [
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      "epoch": 1,
      "event": "opt_step",
      "grad_norm": 0.1994,
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      "lr_a": 1.4e-07,
      "opt_step": 1,
      "rkl_loss": 0.7089,
      "total_opt_steps": 280,
      "unique_active_tokens": 3114274
    },
    {
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      "ce_loss": 0.3909,
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      "grad_norm": 0.2933,
      "loss": 0.5785,
      "lr_a": 2.9e-07,
      "opt_step": 2,
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      "cispo_loss": 0.0,
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      "rkl_loss": 0.447,
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}