readme: ---
  tags:
  - LunarLander-v2
  - ppo
  - deep-reinforcement-learning
  - reinforcement-learning
  - custom-implementation
  - deep-rl-class
  model-index:
  - name: PPO
    results:
    - task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: LunarLander-v2
        type: LunarLander-v2
      metrics:
      - type: mean_reward
        value: -33.15 +/- 17.80
        name: mean_reward
        verified: false
  ---
  
    # PPO Agent Playing LunarLander-v2
  
    This is a trained model of a PPO agent playing LunarLander-v2.
    To learn to code your own PPO agent and train it Unit 8 of the Deep Reinforcement Learning Class: https://github.com/huggingface/deep-rl-class/tree/main/unit8
    
    # Hyperparameters
    ```python
    {'exp_name': 'ppo'
  'seed': 1
  'torch_deterministic': True
  'cuda': True
  'track': False
  'wandb_project_name': 'cleanRL'
  'wandb_entity': None
  'capture_video': False
  'env_id': 'LunarLander-v2'
  'total_timesteps': 250000
  'learning_rate': 0.00025
  'num_envs': 2
  'num_steps': 128
  'anneal_lr': True
  'gae': True
  'gamma': 0.99
  'gae_lambda': 0.95
  'num_minibatches': 4
  'update_epochs': 4
  'norm_adv': True
  'clip_coef': 0.2
  'clip_vloss': True
  'ent_coef': 0.01
  'vf_coef': 0.5
  'max_grad_norm': 0.5
  'target_kl': None
  'repo_id': 'Terence3927/ppo-LunarLander-v2'
  'batch_size': 256
  'minibatch_size': 64}
    ```
    