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Trained / exported adapter / adapter-e4b_pure_opd_v6b_ep2_norm020

e4b_pure_opd_v6b_ep2_norm020

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

When

Recorded date: 2026-11-02

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

Training run day: 2026-11-02 (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?

Test shrinking the epoch-two update toward the unedited base.

Which part changed?

Adapter matrices over the frozen base, targeting: ^model\.language_model\.layers\.\d+\.(self_attn\.(q_proj|k_proj|v_proj|o_proj)|mlp\.(gate_proj|up_proj|down_proj))$

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

How was it changed?

Post-training epoch-two v6b variant with recorded norm 0.20; exact creation time is unavailable. Exported low-rank adapter, rank 64, scaling alpha 32.

Did it improve?

Historical measurements · Historical local result: 12/45 on holdout45; archived Kaggle score: 0.05. The local selection did not establish general improvement.

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 They may contain original predictions and superseded counts; use the measured-outcome summary and corrections above for the current result.

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_v6b_ep2_norm020",
  "wrx90_path": "/home/keith/gemma-v2/adapters/e4b_pure_opd_v6b_ep2_norm020",
  "files": {
    "adapter_model.safetensors": {
      "size_bytes": 279129832,
      "sha256": "70a4b7a2aebf3f3934bdcca33a65e8efb46f9ddcabb54ad2fdc04e9549990cce"
    }
  }
}