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wuc1/
sarm_current_only_full_dataset

Name: sarm_current_only_full_dataset
Availability: InStock

wuc1/bi_so101_ffp_20260603_200349_subtask

apache-2.0

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Reward Model Card for sarm

A Success-Aware Reward Model (SARM) predicts a dense reward signal from observations, typically used downstream for reinforcement learning or human-in-the-loop fine-tuning when task success is not directly observable.

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

How to Get Started with the Reward Model

Train from scratch

bash

lerobot-train \
  --dataset.repo_id=${HF_USER}/<dataset> \
  --reward_model.type=sarm \
  --output_dir=outputs/train/<desired_reward_model_repo_id> \
  --job_name=lerobot_reward_training \
  --reward_model.device=cuda \
  --reward_model.repo_id=${HF_USER}/<desired_reward_model_repo_id> \
  --wandb.enable=true

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

Load the reward model in Python

python

from lerobot.rewards import make_reward_model

reward_model = make_reward_model(pretrained_path="<hf_user>/<reward_model_repo_id>")
reward = reward_model.compute_reward(batch)

Model Details

License: apache-2.0

wuc1/sarm_current_only_full_dataset