
  # 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}
  ```
  
{"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}]}]}]}
LunarLander-v2 ppo deep-reinforcement-learning reinforcement-learning custom-implementation deep-rl-course model-index region:us