(CleanRL) DQN Agent Playing LunarLander-v2
This is a trained model of a DQN agent playing LunarLander-v2. 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[LunarLander-Show]"
python -m cleanrl_utils.enjoy --exp-name LunarLander-Show --env-id LunarLander-v2
Please refer to the documentation for more detail.
Command to reproduce the training
curl -OL https://huggingface.co/odiaz1066/LunarLander-v2-LunarLander-Show-seed42/raw/main/dqn.py
curl -OL https://huggingface.co/odiaz1066/LunarLander-v2-LunarLander-Show-seed42/raw/main/pyproject.toml
curl -OL https://huggingface.co/odiaz1066/LunarLander-v2-LunarLander-Show-seed42/raw/main/poetry.lock
poetry install --all-extras
python dqn.py --track --save-model --capture-video --exp-name LunarLander-Show --seed 42 --env-id LunarLander-v2 --upload-model --hf-entity odiaz1066
Hyperparameters
{'batch_size': 128,
'buffer_size': 10000,
'capture_video': True,
'cuda': True,
'end_e': 0.05,
'env_id': 'LunarLander-v2',
'exp_name': 'LunarLander-Show',
'exploration_fraction': 0.5,
'gamma': 0.99,
'hf_entity': 'odiaz1066',
'learning_rate': 0.00025,
'learning_starts': 10000,
'num_envs': 1,
'save_model': True,
'seed': 42,
'start_e': 1,
'target_network_frequency': 500,
'tau': 1.0,
'torch_deterministic': True,
'total_timesteps': 500000,
'track': True,
'train_frequency': 10,
'upload_model': True,
'wandb_entity': None,
'wandb_project_name': 'lagomorph'}
Evaluation results
- mean_reward on LunarLander-v2self-reported227.09 +/- 33.24