# PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2.
# 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': 5000000 'learning_rate': 0.001 'num_envs': 32 'num_steps': 512 'anneal_lr': True 'gae': True 'gamma': 0.999 'gae_lambda': 0.97 'num_minibatches': 128 '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': 'utyug1/ppo-LunarLander-v2' 'batch_size': 16384 'minibatch_size': 128} ```
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Evaluation results
- mean_reward on LunarLander-v2self-reported271.06 +/- 21.00