mschoi/ai-rfm
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Document multi-layer diagnosis workflow.

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Update project guidelines and attempt log to require multi-view analysis (metrics, trajectory behavior, structural diagnostics) instead of metric-only decision making.

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demian3b
2026-04-16 17:28:46 +09:00
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@@ -48,3 +48,4 @@ This repository is intentionally pinned to CUDA 12.6 PyTorch wheels and matching
- 2026-04-16: Added model-type support (`gcn`/`mlp`) and time-sampling control; best current run is `gcn hidden=512 layers=8 batch=96` with `mean_rmsd_100=2.523552`.
- 2026-04-16: Added pre-commit artifact refresh: on best update it now stages `BEST_PRACTICE.json`, `artifacts/best_model.pt`, and regenerates 6 trajectory visualizations in `reports/trajectories/`.
- 2026-04-16: Enforced random-time flow-matching rule (no fixed training time), saved best checkpoint to git-tracked artifact path, and improved metric to `mean_rmsd_100=2.519821` with `gcn hidden=512 layers=8 batch=96`.
- 2026-04-16: Added a general multi-layer diagnosis principle to `GUIDELINES.md` so experiments are judged with quantitative + qualitative + structural evidence, not metric-only optimization.