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(CleanRL) DDPG Agent Playing MountainCarContinuous-v0

This is a trained model of a DDPG agent playing MountainCarContinuous-v0. The model was trained by using CleanRL and the most up-to-date training code can be found here.

Get Started

To use this model, please install the cleanrl package with the following command:

pip install "cleanrl[ddpg_continuous_action]"
python -m cleanrl_utils.enjoy --exp-name ddpg_continuous_action --env-id MountainCarContinuous-v0

Please refer to the documentation for more detail.

Command to reproduce the training

curl -OL https://huggingface.co/nsanghi/MountainCarContinuous-v0-ddpg_continuous_action-seed1/raw/main/ddpg_continuous_action.py
curl -OL https://huggingface.co/nsanghi/MountainCarContinuous-v0-ddpg_continuous_action-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/nsanghi/MountainCarContinuous-v0-ddpg_continuous_action-seed1/raw/main/poetry.lock
poetry install --all-extras
python ddpg_continuous_action.py --no-cuda --total-timesteps 25000 --learning-starts 5000 --env-id MountainCarContinuous-v0 --track --hf-entity nsanghi --capture-video --save-model --upload-model

Hyperparameters

{'batch_size': 256,
 'buffer_size': 1000000,
 'capture_video': True,
 'cuda': False,
 'env_id': 'MountainCarContinuous-v0',
 'exp_name': 'ddpg_continuous_action',
 'exploration_noise': 0.1,
 'gamma': 0.99,
 'hf_entity': 'nsanghi',
 'learning_rate': 0.0003,
 'learning_starts': 5000,
 'noise_clip': 0.5,
 'policy_frequency': 2,
 'save_model': True,
 'seed': 1,
 'tau': 0.005,
 'torch_deterministic': True,
 'total_timesteps': 25000,
 'track': True,
 'upload_model': True,
 'wandb_entity': None,
 'wandb_project_name': 'cleanRL'}
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Evaluation results

  • mean_reward on MountainCarContinuous-v0
    self-reported
    -1.00 +/- 0.04