| | --- |
| | 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: 153.00 +/- 43.64 |
| | name: mean_reward |
| | verified: false |
| | --- |
| | |
| | # PPO Agent Playing CartPole-v1 |
| |
|
| | This is a trained model of a PPO agent playing CartPole-v1. |
| |
|
| | # Hyperparameters |
| | ```python |
| | {'exp_name': 'unit8_part1' |
| | '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': 50000 |
| | 'learning_rate': 0.00025 |
| | 'num_envs': 4 |
| | 'num_steps': 128 |
| | 'anneal_lr': True |
| | 'gae': True |
| | 'gamma': 0.99 |
| | 'gae_lambda': 0.95 |
| | 'num_minibatches': 4 |
| | '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': 'Huinker/ppo-CartPole-v1' |
| | 'batch_size': 512 |
| | 'minibatch_size': 128} |
| | ``` |
| | |
