---
tags:
- LunarLander-v2
- ppo
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
- deep-rl-course
model-index:
- name: PPO
  results:
  - task:
      type: reinforcement-learning
      name: reinforcement-learning
    dataset:
      name: LunarLander-v2
      type: LunarLander-v2
    metrics:
    - type: mean_reward
      value: 230.81 +/- 20.92
      name: mean_reward
      verified: false
---

  # PPO Agent Playing LunarLander-v2

  This is a trained model of a PPO agent playing LunarLander-v2.

  # Hyperparameters
  ```python
  {'path': '/content/drive/MyDrive/Colab Notebooks/HuggingFace/RL/Unit08'
'name': 'ppo-LunaLander_1.pt'
'env-id': 'LunarLander-v2'
'agent_properties': {'num_layers': 2
'hidden': 128
'activation': 'Tanh'}
'seed': ''
'device': 'cuda'
'total_timesteps': 100000
'num_steps': 32768
'batch_size': 64
'update_epochs': 2
'learning_rate': 1e-05
'lr_schedule': 'Exp'
'lr_final': 1e-06
'gamma': 0.995
'gae_lambda': 0.99
'norm_adv': 'True'
'clip_coef': 0.2
'clip_vloss': 'False'
'entropy_loss_coef': 0.01
'value_loss_coef': 0.5
'max_grad_norm': 0.5
'n_eval_episodes': 10}
  ```