Shiki42/ctr-act-pick-dual-bottles-sequential-idlemask-e337-step30000

DEPRECATED / 已废弃 — E337

Do not use this checkpoint or any evaluation results derived from it.

废弃原因：它们错误地开启了 idle mask，而且 idle mask 的定义也不正确。

This checkpoint was trained on a non-CTR dataset with IdleMask incorrectly enabled, and the IdleMask definition itself was incorrect. All checkpoints from this training run, including intermediate checkpoints and published copies, and all associated evaluation metrics are deprecated. Historical success rates, verification PASS receipts, and archive approvals are retained for provenance only and do not establish scientific validity or eligibility for reuse.

Changing inference settings or the card does not repair the trained checkpoint. Use a newly trained checkpoint with the correct non-CTR training recipe and IdleMask disabled, followed by a separate evaluation.

Deprecation authorized by the repository owner on 2026-09-19. This notice supersedes any earlier eligibility or reuse statements below. Original weights, configuration, and historical results are retained.

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E337 — Pick Dual Bottles / sequential

Inference checkpoint at 30000 optimizer updates. Training Run: E337-R002.

Closed-loop evaluation has not been reported for this checkpoint.

Training identity

• Dataset: CTR-local/q123-sequential-20260919
• Revision: aa3e76fc5dc959231311465c6478c82c77620b0f
• Camera preset: centered_fovy90 calibrated wrist cameras.
• IdleMask: enabled; inactive arm loss weight zero.
• Exact configuration and source identities: ctr-provenance.json and resolved configuration.

Loading and limitations

LeRobot v0.4.4 ACT checkpoint, commit 8fff0fde7c79f23a93d845d1a50e985de01f8b8a. Use the included model and pre/postprocessors with measured 14-D state and the frozen camera/action conventions. CPU model restore is checked separately; full optimizer restore and closed-loop ability are separate qualifications.

No optimizer state is included. SHA256SUMS identifies every public payload file. Source checkpoint and training logs remain preserved on the training machine. Training completion and raw evaluation result archival do not establish deployment safety or scientific causal conclusions.