---
tags:
- CartPole-v1
- 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: CartPole-v1
      type: CartPole-v1
    metrics:
    - type: mean_reward
      value: 225.90 +/- 71.33
      name: mean_reward
      verified: false
---

  # PPO Agent Playing CartPole-v1

  This is a trained model of a PPO agent playing CartPole-v1.
    
  # Hyperparameters
  ```python
  {'fff': '/root/.local/share/jupyter/runtime/kernel-679339ac-acc2-4e2c-b7e7-f3d6dda737bb.json'
'exp_name': 'tempname'
'seed': 1
'torch_deterministic': True
'cuda': True
'track': False
'wandb_project_name': 'cleanRL'
'wandb_entity': None
'capture_video': False
'env_id': 'CartPole-v1'
'total_timesteps': 900000
'learning_rate': 0.000205
'num_envs': 6
'num_steps': 384
'anneal_lr': True
'gae': True
'gamma': 0.985
'gae_lambda': 0.94
'num_minibatches': 4
'update_epochs': 4
'norm_adv': True
'clip_coef': 0.225
'clip_vloss': True
'ent_coef': 0.01
'vf_coef': 0.5
'max_grad_norm': 0.5
'target_kl': None
'repo_id': 'kaljr/ppo-CartPole-v1'
'batch_size': 2304
'minibatch_size': 576}
  ```