--- tags: - CartPole-v1 - deep-reinforcement-learning - reinforcement-learning - custom-implementation library_name: cleanrl model-index: - name: DQPN_freq results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: CartPole-v1 type: CartPole-v1 metrics: - type: mean_reward value: 482.67 +/- 0.00 name: mean_reward verified: false --- # (CleanRL) **DQPN_freq** Agent Playing **CartPole-v1** This is a trained model of a DQPN_freq agent playing CartPole-v1. 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/CP_DQPN_x2.py). ## Get Started To use this model, please install the `cleanrl` package with the following command: ``` pip install "cleanrl[CP_DQPN_x2]" python -m cleanrl_utils.enjoy --exp-name CP_DQPN_x2 --env-id CartPole-v1 ``` 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/pfunk/CartPole-v1-CP_DQPN_x2-seed410/raw/main/dqpn_freq.py curl -OL https://huggingface.co/pfunk/CartPole-v1-CP_DQPN_x2-seed410/raw/main/pyproject.toml curl -OL https://huggingface.co/pfunk/CartPole-v1-CP_DQPN_x2-seed410/raw/main/poetry.lock poetry install --all-extras python dqpn_freq.py --track --wandb-entity pfunk --wandb-project-name dqpn --capture-video true --save-model true --upload-model true --hf-entity pfunk --exp-name CP_DQPN_x2 --policy-network-frequency 200 --seed 410 ``` # Hyperparameters ```python {'alg_type': 'dqpn_freq.py', 'batch_size': 256, 'buffer_size': 300000, 'capture_video': True, 'cuda': True, 'end_e': 0.1, 'env_id': 'CartPole-v1', 'exp_name': 'CP_DQPN_x2', 'exploration_fraction': 0.2, 'gamma': 1.0, 'hf_entity': 'pfunk', 'learning_rate': 0.0001, 'learning_starts': 1000, 'policy_network_frequency': 200, 'policy_tau': 1.0, 'save_model': True, 'seed': 410, 'start_e': 1.0, 'target_network_frequency': 100, 'target_tau': 1.0, 'torch_deterministic': True, 'total_timesteps': 500000, 'track': True, 'train_frequency': 1, 'upload_model': True, 'wandb_entity': 'pfunk', 'wandb_project_name': 'dqpn'} ```