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Stevenshuqing/
LW-Bench-ACT

Name: LW-Bench-ACT
Rating: 2.5 (14 reviews)

LightwheelAI/Lightwheel-Tasks-X7S

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LW-Bench ACT 5K for X7s

LeRobot ACT policy trained from scratch on the audited X7s strict compositional split in LW-Compositional-Bench.

Training contract

Dataset: LightwheelAI/Lightwheel-Tasks-X7S
Train split: 91 clean tasks; tasks 7, 119, and 149 held out
Inputs: three RGB cameras plus 25D robot state
Output: native 21D X7s absolute action
Hardware: 4 GPUs
Seed: 1000
Effective global batch: 64
Checkpoint: 5,000 global optimizer updates
Evaluation horizon: first 16 valid action steps

Offline 5K results

Metric	Value
H16 MAE	0.077566
H16 RMSE	0.163998
Gripper balanced accuracy	94.73%
Boundary-proxy MAE	0.109228
Interior MAE	0.071501
Boundary / interior MAE	1.528x

These results cover three strict held-out tasks and are descriptive. Offline action error does not replace closed-loop success evaluation.

Load with LeRobot

python

from lerobot.policies.act.modeling_act import ACTPolicy

policy = ACTPolicy.from_pretrained("Stevenshuqing/LW-Bench-ACT")
policy.eval()

Use LeRobot 0.4.3 and the included preprocessor/postprocessor files. The repository contains the complete pretrained_model directory produced by LeRobot.

Provenance

Code and protocol: https://github.com/stevenqing/LW-Compositional-Bench
Full report: https://github.com/stevenqing/LW-Compositional-Bench/blob/main/artifacts/model-eval/x7s/rotation-v0/budget-5k/report.md
Code revision: 2d0e26dd2fe2e91046f416bd65bc369f8568d7f0
model.safetensors SHA256: dffc7c1801b77a53c18fe3f78627aa742ec0d158e0ece5b78737ca4edab6dfa4

Limitations

This checkpoint is specific to the X7s observation/action schema. The benchmark is offline because the available A100 GPUs cannot provide Isaac Sim RT camera rendering. Transition boundaries are action-space proxies based on gripper sign changes and robust continuous-action peaks, not human semantic annotations.