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---
tags:
- InvertedPendulum-v4
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: PPO
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: InvertedPendulum-v4
type: InvertedPendulum-v4
metrics:
- type: mean_reward
value: 5.30 +/- 0.46
name: mean_reward
verified: false
---
# (CleanRL) **PPO** Agent Playing **InvertedPendulum-v4**
This is a trained model of a PPO agent playing InvertedPendulum-v4.
The model was trained by using [CleanRL](https://github.com/vwxyzjn/cleanrl) and the most up-to-date training code can be
found [here](https://github.com/vwxyzjn/cleanrl/blob/master/cleanrl/ppo_continuous_action.py).
## Get Started
To use this model, please install the `cleanrl` package with the following command:
```
pip install "cleanrl[ppo_continuous_action]"
python -m cleanrl_utils.enjoy --exp-name ppo_continuous_action --env-id InvertedPendulum-v4
```
Please refer to the [documentation](https://docs.cleanrl.dev/get-started/zoo/) for more detail.
## Command to reproduce the training
```bash
curl -OL https://huggingface.co/cleanrl/InvertedPendulum-v4-ppo_continuous_action-seed1/raw/main/ppo_continuous_action.py
curl -OL https://huggingface.co/cleanrl/InvertedPendulum-v4-ppo_continuous_action-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/cleanrl/InvertedPendulum-v4-ppo_continuous_action-seed1/raw/main/poetry.lock
poetry install --all-extras
python ppo_continuous_action.py --track --save-model --upload-model --hf-entity cleanrl --env-id InvertedPendulum-v4 --seed 1
```
# Hyperparameters
```python
{'anneal_lr': True,
'batch_size': 2048,
'capture_video': False,
'clip_coef': 0.2,
'clip_vloss': True,
'cuda': True,
'ent_coef': 0.0,
'env_id': 'InvertedPendulum-v4',
'exp_name': 'ppo_continuous_action',
'gae_lambda': 0.95,
'gamma': 0.99,
'hf_entity': 'cleanrl',
'learning_rate': 0.0003,
'max_grad_norm': 0.5,
'minibatch_size': 64,
'norm_adv': True,
'num_envs': 1,
'num_minibatches': 32,
'num_steps': 2048,
'save_model': True,
'seed': 1,
'target_kl': None,
'torch_deterministic': True,
'total_timesteps': 1000000,
'track': True,
'update_epochs': 10,
'upload_model': True,
'vf_coef': 0.5,
'wandb_entity': None,
'wandb_project_name': 'cleanRL'}
```
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