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---
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: -27.96 +/- 50.99
name: mean_reward
verified: false
---
# PPO Agent Playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2.
# Hyperparameters
```python
{'exp_name': '/home/zz/DOD/DeepRL/HuggingFaceCourse/Proximal Policy Optimization'
'seed': 1
'torch_deterministic': True
'cuda': True
'track': False
'wandb_project_name': 'ppoLunarLander'
'wandb_entity': None
'capture_video': False
'env_id': 'LunarLander-v2'
'total_timesteps': 500000
'learning_rate': 5e-05
'num_envs': 8
'num_steps': 1024
'anneal_lr': True
'gae': True
'gamma': 0.999
'gae_lambda': 0.956973
'num_minibatches': 128
'update_epochs': 4
'norm_adv': True
'clip_coef': 0.384411
'clip_vloss': True
'ent_coef': 0.01
'vf_coef': 0.686165
'max_grad_norm': 0.5
'target_kl': 0.01
'repo_id': 'zzen0008/ppo-LunarLander-v2'
'batch_size': 8192
'minibatch_size': 64}
```
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