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10 changes: 5 additions & 5 deletions research/classifier/measurements-meta.json
Original file line number Diff line number Diff line change
@@ -1,17 +1,17 @@
{
"_note": "Hand-recorded from the v0.2.0 collection run done on the author's laptop before the audit fields were added to collect_measurements.py. Future runs will populate this file automatically, with per-cell tokens + wall-clock aggregated by the collector. Fields with `null` are unknown for this specific run; everything else came from the PR description (#1) and the row count of measurements.csv.",
"_note": "Hand-recorded from the v0.2.0 collection run done on the author's laptop before the audit fields were added to collect_measurements.py. Future runs will populate this file automatically, with per-cell tokens + wall-clock aggregated by the collector. Token totals remain `null` because the OpenAI-compat `usage` block was not persisted during this run; the started_at / ended_at / wall_clock_s fields below are *reconstructed* from the modification timestamps of the run's stdout log file (`/tmp/mnemoscope-full.log` on the author's machine), not measured by the collector — they bound the wall-clock but include any time the orchestrator spent idle between cells.",
"model": "gemma4-ctx:latest",
"model_base": "gemma4:26b",
"model_quantization": "Q4_K_M",
"model_context_window": 40000,
"endpoint": "http://localhost:11434/v1",
"endpoint_kind": "ollama",
"offline": false,
"started_at": null,
"ended_at": null,
"wall_clock_s": null,
"started_at": "2026-04-29T04:11:20-04:00",
"ended_at": "2026-04-30T03:13:50-04:00",
"wall_clock_s": 82950,
"wall_clock_s_grading_only": null,
"wall_clock_human": "multi-hour, single-machine local run",
"wall_clock_human": "23h02m30s end-to-end (reconstructed from log file mtime, not measured by collector)",
"variants_attempted": 50,
"variants_kept": 50,
"variants_skipped_no_needles": 0,
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12 changes: 6 additions & 6 deletions research/classifier/model.json
Original file line number Diff line number Diff line change
Expand Up @@ -23,27 +23,27 @@
},
"rows_train": 40,
"rows_test": 10,
"onnx_round_trip_max_delta": 1.5894571991914574e-08,
"onnx_round_trip_max_delta": 1.5894571880892272e-08,
"data_source": "classifier/measurements.csv",
"seed": 42,
"grader_models": [
"gemma4-ctx:latest"
],
"offline_rows": 0,
"dataset_collection": {
"_note": "Hand-recorded from the v0.2.0 collection run done on the author's laptop before the audit fields were added to collect_measurements.py. Future runs will populate this file automatically, with per-cell tokens + wall-clock aggregated by the collector. Fields with `null` are unknown for this specific run; everything else came from the PR description (#1) and the row count of measurements.csv.",
"_note": "Hand-recorded from the v0.2.0 collection run done on the author's laptop before the audit fields were added to collect_measurements.py. Future runs will populate this file automatically, with per-cell tokens + wall-clock aggregated by the collector. Token totals remain `null` because the OpenAI-compat `usage` block was not persisted during this run; the started_at / ended_at / wall_clock_s fields below are *reconstructed* from the modification timestamps of the run's stdout log file (`/tmp/mnemoscope-full.log` on the author's machine), not measured by the collector \u2014 they bound the wall-clock but include any time the orchestrator spent idle between cells.",
"model": "gemma4-ctx:latest",
"model_base": "gemma4:26b",
"model_quantization": "Q4_K_M",
"model_context_window": 40000,
"endpoint": "http://localhost:11434/v1",
"endpoint_kind": "ollama",
"offline": false,
"started_at": null,
"ended_at": null,
"wall_clock_s": null,
"started_at": "2026-04-29T04:11:20-04:00",
"ended_at": "2026-04-30T03:13:50-04:00",
"wall_clock_s": 82950,
"wall_clock_s_grading_only": null,
"wall_clock_human": "multi-hour, single-machine local run",
"wall_clock_human": "23h02m30s end-to-end (reconstructed from log file mtime, not measured by collector)",
"variants_attempted": 50,
"variants_kept": 50,
"variants_skipped_no_needles": 0,
Expand Down