--- tags: - Ant-v4 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: SAC results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Ant-v4 type: Ant-v4 metrics: - type: mean_reward value: 4623.14 +/- 1360.99 name: mean_reward verified: false --- # (CleanRL) **SAC** Agent Playing **Ant-v4** This is a trained model of a SAC agent playing Ant-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/sac_continuous_action.py). ## Get Started To use this model, please install the `cleanrl` package with the following command: ``` pip install "cleanrl[sac_continuous_action]" python -m cleanrl_utils.enjoy --exp-name sac_continuous_action --env-id Ant-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/Ant-v4-sac_continuous_action-seed5/raw/main/sac_continuous_action.py curl -OL https://huggingface.co/sdpkjc/Ant-v4-sac_continuous_action-seed5/raw/main/pyproject.toml curl -OL https://huggingface.co/sdpkjc/Ant-v4-sac_continuous_action-seed5/raw/main/poetry.lock poetry install --all-extras python sac_continuous_action.py --save-model --upload-model --hf-entity sdpkjc --env-id Ant-v4 --seed 5 --track ``` # Hyperparameters ```python {'alpha': 0.2, 'autotune': True, 'batch_size': 256, 'buffer_size': 1000000, 'capture_video': False, 'cuda': True, 'env_id': 'Ant-v4', 'exp_name': 'sac_continuous_action', 'gamma': 0.99, 'hf_entity': 'sdpkjc', 'learning_starts': 5000.0, 'noise_clip': 0.5, 'policy_frequency': 2, 'policy_lr': 0.0003, 'q_lr': 0.001, 'save_model': True, 'seed': 5, 'target_network_frequency': 1, 'tau': 0.005, 'torch_deterministic': True, 'total_timesteps': 1000000, 'track': True, 'upload_model': True, 'wandb_entity': None, 'wandb_project_name': 'cleanRL'} ```