jungfrauandClaude Fable 5.1 f1a945528e cluster runs on dataset v3: resolution and model-size levers ...

Three ledger runs for the cluster, exported on dataset/2026-09-29_v3 with the
promoted recipe: nano at 1024 px, small at 640 px, small at 1024 px. A run can
now carry its own training arguments (train_args in run.json, set with
ledger new --kv), which train_run.py applies under any --set; train.sbatch
forwards extra arguments after the run id (e.g. --batch 8). yolo26s-seg.pt
joins the base weights under LFS. slurm/README lists the runs, the questions
they answer and the commands.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

2026-09-30 07:18:06 +02:00

..

__init__.py

training loop: run ledger, studio export importer with an image pool, train_run with gold gate and auto-promotion, SLURM template, CI

2026-09-28 16:06:06 +02:00

import_studio_export.py

training loop: run ledger, studio export importer with an image pool, train_run with gold gate and auto-promotion, SLURM template, CI

2026-09-28 16:06:06 +02:00

ledger.py

training loop: run ledger, studio export importer with an image pool, train_run with gold gate and auto-promotion, SLURM template, CI

2026-09-28 16:06:06 +02:00

measure_weights.py

measure_weights: gold measure of any weights into the registry (the gate's baseline)

2026-09-28 16:48:24 +02:00

train_run.py

cluster runs on dataset v3: resolution and model-size levers

2026-09-30 07:18:06 +02:00