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docs(g05): record real training smoke

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Pepijn
2026-07-28 21:43:47 +02:00
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@@ -173,6 +173,11 @@ uv run pytest tests/policies/g05 tests/runtime/test_g05_adapter.py -q
uv run ruff check src/lerobot/policies/g05 tests/policies/g05 uv run ruff check src/lerobot/policies/g05 tests/policies/g05
``` ```
An RTX 5090 smoke test loaded the real private `g05_libero` checkpoint and
completed a batch-size-one BF16 forward, backward, gradient clip, and AdamW
step. It produced finite loss `2.77356`, finite pre-clip gradient norm `54.38`,
all six author optimizer groups, and 23.59 GiB peak allocated CUDA memory.
A 50-episode LIBERO/RoboTwin success-rate comparison additionally requires the A 50-episode LIBERO/RoboTwin success-rate comparison additionally requires the
matching simulator, task assets, reset seeds, and author evaluator; no task-level matching simulator, task assets, reset seeds, and author evaluator; no task-level
benchmark number is claimed until that separate gate runs. benchmark number is claimed until that separate gate runs.