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arclabmit/
xarm7_act_beavrsim_pickplace_model

Name: xarm7_act_beavrsim_pickplace_model
Availability: InStock

arclabmit/xarm7_beavrsim_pickplace_dataset

2304.13705

apache-2.0

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Model Card for act

Action Chunking with Transformers (ACT) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates.

This policy has been trained and pushed to the Hub using LeRobot. See the full documentation at LeRobot Docs.

How to Get Started with the Model

For a complete walkthrough, see the training guide. Below is the short version on how to train and run inference/eval:

Train from scratch

bash

lerobot-train \
  --dataset.repo_id=${HF_USER}/<dataset> \
  --policy.type=act \
  --output_dir=outputs/train/<desired_policy_repo_id> \
  --job_name=lerobot_training \
  --policy.device=cuda \
  --policy.repo_id=${HF_USER}/<desired_policy_repo_id>
  --wandb.enable=true

Writes checkpoints to outputs/train/<desired_policy_repo_id>/checkpoints/.

Evaluate the policy/run inference

bash

lerobot-record \
  --robot.type=so100_follower \
  --dataset.repo_id=<hf_user>/eval_<dataset> \
  --policy.path=<hf_user>/<desired_policy_repo_id> \
  --episodes=10

Prefix the dataset repo with eval_ and supply --policy.path pointing to a local or hub checkpoint.

Model Details

License: apache-2.0

Evaluation Results

Evaluated on 2026-01-27 12:11

Metric	Value
Success Rate	69.6%
Average Reward	7.147
Max Reward (Avg)	6.963
Episodes	1000
Eval Speed	1.55 s/ep
Seed	26

[!TIP] Detailed per-episode results can be found in eval/eval_info.json.

arclabmit/xarm7_act_beavrsim_pickplace_model