metadata
tags:
- BreakoutNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: RAINBOW
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: BreakoutNoFrameskip-v4
type: BreakoutNoFrameskip-v4
metrics:
- type: mean_reward
value: 4.50 +/- 4.50
name: mean_reward
verified: false
(CleanRL) RAINBOW Agent Playing BreakoutNoFrameskip-v4
This is a trained model of a RAINBOW agent playing BreakoutNoFrameskip-v4. The model was trained by using CleanRL and the most up-to-date training code can be found here.
Get Started
To use this model, please install the cleanrl
package with the following command:
pip install "cleanrl[rainbow_atari]"
python -m cleanrl_utils.enjoy --exp-name rainbow_atari --env-id BreakoutNoFrameskip-v4
Please refer to the documentation for more detail.
Command to reproduce the training
curl -OL https://huggingface.co/qgallouedec/BreakoutNoFrameskip-v4-rainbow_atari-seed1/raw/main/rainbow_atari.py
curl -OL https://huggingface.co/qgallouedec/BreakoutNoFrameskip-v4-rainbow_atari-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/qgallouedec/BreakoutNoFrameskip-v4-rainbow_atari-seed1/raw/main/poetry.lock
poetry install --all-extras
python rainbow_atari.py --learning-starts 100 --total-timesteps 5000 --save-model --upload-model --hf-entity qgallouedec
Hyperparameters
{'batch_size': 32,
'buffer_size': 1000000,
'capture_video': False,
'cuda': True,
'env_id': 'BreakoutNoFrameskip-v4',
'exp_name': 'rainbow_atari',
'gamma': 0.99,
'hf_entity': 'qgallouedec',
'learning_rate': 0.00025,
'learning_starts': 100,
'n_atoms': 51,
'num_envs': 1,
'save_model': True,
'seed': 1,
'target_network_frequency': 10000,
'torch_deterministic': True,
'total_timesteps': 5000,
'track': False,
'train_frequency': 4,
'upload_model': True,
'v_max': 10,
'v_min': -10,
'wandb_entity': None,
'wandb_project_name': 'cleanRL'}