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chennana1028/
gwp05-openarm-sbint-abs-step50000

Name: gwp05-openarm-sbint-abs-step50000
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GigaWorld-Policy-0.5 · SBInt OpenArm (step 50000, absolute)

Fine-tuned GigaWorld-Policy-0.5 MoT transformer on SBInt openarm002 (873 episodes, 16-dim absolute joints, left-first packing), continued from step 20000 to 50000.

Sibling of the delta ckpt chennana1028/gwp05-openarm-sbint-delta-step50000. Same data / T5 / cameras / dims; only the action semantics differ:

All 16 dims: absolute joint targets — delta_mask = [False]*16
Left-first packing: [larm7, lgrip, rarm7, rgrip], gripper dims 7 and 15

Use with --action-mode abs and the matching norm_stats_sbint_abs.json in this repo. Mixing the delta norm stats gives ~10x scale errors (the scripts warn but do not abort).

File	Notes
`config.json`	`CasualWorldActionTransformer_MoT`, `in/out_action_channels=16`
`diffusion_pytorch_model.bin`	EMA weights, train job `4335486` step 50000 (continued from `4306868` step 20000)
`norm_stats_sbint_abs.json`	Matching absolute-joint quantile norm stats

Training snapshot

Jobs: Slurm 4306868 (0-20k) + 4335486 (20k-50k) on 002-partition-RAD, 2x8 H100
Steps: 50000 · ckpt every 1000 · eff batch 128
Data: SBInt openarm002, LeRobot v3 (873 ep), task: place object in box + close lid
Base: HF GWP-0.5 + Wan-class Diffusers VAE (lingbot_va_base)

Open-loop eval (episode 740, replan 48)

ckpt	MAE	seam ratio
abs step 50000 (this repo)	0.0130	3.67x
delta step 50000	0.0101	2.25x

chennana1028/gwp05-openarm-sbint-abs-step50000

GigaWorld-Policy-0.5 · SBInt OpenArm (step 50000, absolute)

Contents

Training snapshot

Open-loop eval (episode 740, replan 48)

chennana1028/
gwp05-openarm-sbint-abs-step50000