Bi-LaWM RoboTwin Stage3-Only — Policy From Scratch

Repository: GT-111/bi-lawm-robotwin-stage3-only (renamed from lawam-robotwin-steps68000 on 2026-08-31; the old URL redirects here).

Intermediate checkpoints from the RoboTwin Stage3-only policy-from-scratch training run of Bi-LaWM.

The Stage3 policy was trained without a pretrained policy checkpoint. It uses the RoboTwin Stage1 BiLAM export as its latent-action model initialization, so “from scratch” here refers specifically to the policy training stage rather than the complete Bi-LaWM stack.

Checkpoints

Hub path Training step Format
checkpoints/step-010000/ 10,000 Full sharded FSDP training checkpoint
checkpoints/step-020000/ 20,000 Full sharded FSDP training checkpoint
checkpoints/step-030000/ 30,000 Full sharded FSDP training checkpoint
checkpoints/step-040000/ 40,000 Full sharded FSDP training checkpoint
checkpoints/step-050000/ 50,000 Full sharded FSDP training checkpoint
checkpoints/step-060000/ 60,000 Full sharded FSDP training checkpoint
checkpoints/step-068000/ 68,000 Latest published full sharded FSDP training checkpoint

Each checkpoint contains the model shards, per-rank optimizer and RNG states, scheduler state, and trainer_state.json. These are resumable distributed-training checkpoints rather than merged inference-only weights.

Experiment

  • Project: Bi-LaWM
  • Dataset/environment: RoboTwin
  • Stage: Stage3 policy training
  • Policy initialization: from scratch (no pretrained policy checkpoint)
  • Latent-action initialization: RoboTwin Stage1 BiLAM export
  • Training plan: 100k steps
  • Published interval: every 10k steps, plus the latest available 68k checkpoint

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Use these checkpoints with the matching Bi-LaWM code and FSDP configuration. For inference or evaluation, export/merge the selected distributed checkpoint with the project checkpoint tooling first.

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