readme: ---
  tags:
  - BreakoutNoFrameskip-v4
  - deep-reinforcement-learning
  - reinforcement-learning
  - custom-implementation
  library_name: cleanrl
  model-index:
  - name: C51
    results:
    - task:
        type: reinforcement-learning
        name: reinforcement-learning
      dataset:
        name: BreakoutNoFrameskip-v4
        type: BreakoutNoFrameskip-v4
      metrics:
      - type: mean_reward
        value: 381.00 +/- 56.35
        name: mean_reward
        verified: false
  ---
  
  # (CleanRL) **C51** Agent Playing **BreakoutNoFrameskip-v4**
  
  This is a trained model of a C51 agent playing BreakoutNoFrameskip-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/c51_atari.py).
  
  ## Get Started
  
  To use this model, please install the `cleanrl` package with the following command:
  
  ```
  pip install "cleanrl[c51_atari]"
  python -m cleanrl_utils.enjoy --exp-name c51_atari --env-id BreakoutNoFrameskip-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/kinalmehta/BreakoutNoFrameskip-v4-c51_atari-seed1/raw/main/c51_atari.py
  curl -OL https://huggingface.co/kinalmehta/BreakoutNoFrameskip-v4-c51_atari-seed1/raw/main/pyproject.toml
  curl -OL https://huggingface.co/kinalmehta/BreakoutNoFrameskip-v4-c51_atari-seed1/raw/main/poetry.lock
  poetry install --all-extras
  python c51_atari.py --save-model --upload-model --hf-entity kinalmehta --env-id BreakoutNoFrameskip-v4
  ```
  
  # Hyperparameters
  ```python
  {'batch_size': 32,
   'buffer_size': 1000000,
   'capture_video': False,
   'cuda': True,
   'end_e': 0.01,
   'env_id': 'BreakoutNoFrameskip-v4',
   'exp_name': 'c51_atari',
   'exploration_fraction': 0.1,
   'gamma': 0.99,
   'hf_entity': 'kinalmehta',
   'learning_rate': 0.00025,
   'learning_starts': 80000,
   'n_atoms': 51,
   'save_model': True,
   'seed': 1,
   'start_e': 1,
   'target_network_frequency': 10000,
   'torch_deterministic': True,
   'total_timesteps': 10000000,
   'track': False,
   'train_frequency': 4,
   'upload_model': True,
   'v_max': 10,
   'v_min': -10,
   'wandb_entity': None,
   'wandb_project_name': 'cleanRL'}
  ```
      