metadata
datasets: alexis779/so100_cube_rectangle_night
library_name: lerobot
license: apache-2.0
model_name: reward_classifier
pipeline_tag: robotics
tags:
- reward_classifier
- reward-model
- robotics
- lerobot
Reward Model Card for reward_classifier
A reward classifier is a lightweight neural network that scores observations or trajectories for task success, providing a learned reward signal or offline evaluation when explicit rewards are unavailable.
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
lerobot-train \
--dataset.repo_id=${HF_USER}/<dataset> \
--reward_model.type=reward_classifier \
--output_dir=outputs/train/<desired_reward_model_repo_id> \
--job_name=lerobot_reward_training \
--reward_model.device=cuda \
--reward_model.repo_id=${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
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