--- tags: - Hopper-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: Hopper-v4 type: Hopper-v4 metrics: - type: mean_reward value: 861.03 +/- 23.36 name: mean_reward verified: false --- # (CleanRL) **PPO** Agent Playing **Hopper-v4** This is a trained model of a PPO agent playing Hopper-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_fix_continuous_action.py). ## Get Started To use this model, please install the `cleanrl` package with the following command: ``` pip install "cleanrl[ppo_fix_continuous_action]" python -m cleanrl_utils.enjoy --exp-name ppo_fix_continuous_action --env-id Hopper-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/sdpkjc/Hopper-v4-ppo_fix_continuous_action-seed4/raw/main/ppo_fix_continuous_action.py curl -OL https://huggingface.co/sdpkjc/Hopper-v4-ppo_fix_continuous_action-seed4/raw/main/pyproject.toml curl -OL https://huggingface.co/sdpkjc/Hopper-v4-ppo_fix_continuous_action-seed4/raw/main/poetry.lock poetry install --all-extras python ppo_fix_continuous_action.py --save-model --upload-model --hf-entity sdpkjc --env-id Hopper-v4 --seed 4 --track ``` # 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': 'Hopper-v4', 'exp_name': 'ppo_fix_continuous_action', 'gae_lambda': 0.95, 'gamma': 0.99, 'hf_entity': 'sdpkjc', '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': 4, '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'} ```