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sb3/ppo-Acrobot-v1
ppo-Acrobot-v1 is a reinforcement learning model from sb3. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for stable-baselines3.
This is a trained model of a PPO agent playing Acrobot-v1 using the stable-baselines3 library and the RL Zoo.
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From the Hugging Face model README
This is a trained model of a PPO agent playing Acrobot-v1 using the stable-baselines3 library and the RL Zoo.
The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo ppo --env Acrobot-v1 -orga sb3 -f logs/
python enjoy.py --algo ppo --env Acrobot-v1 -f logs/
python train.py --algo ppo --env Acrobot-v1 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo ppo --env Acrobot-v1 -f logs/ -orga sb3
OrderedDict([('ent_coef', 0.0),
('gae_lambda', 0.94),
('gamma', 0.99),
('n_envs', 16),
('n_epochs', 4),
('n_steps', 256),
('n_timesteps', 1000000.0),
('normalize', True),
('policy', 'MlpPolicy'),
('normalize_kwargs', {'norm_obs': True, 'norm_reward': False})])