|
--- |
|
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: 449.70 +/- 78.07 |
|
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': 256 |
|
'anneal_lr': True |
|
'gae': True |
|
'gamma': 0.995 |
|
'gae_lambda': 0.95 |
|
'num_minibatches': 4 |
|
'update_epochs': 4 |
|
'norm_adv': True |
|
'clip_coef': 0.195 |
|
'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': 1536 |
|
'minibatch_size': 384} |
|
``` |
|
|