(CleanRL) DQN Agent Playing BreakoutNoFrameskip-v4
This is a trained model of a DQN agent playing BreakoutNoFrameskip-v4. The model was trained by using CleanRL and the training code can be found here.
Hyperparameters
{'batch_size': 32,
'buffer_size': 1000000,
'capture_video': False,
'cuda': True,
'end_e': 0.01,
'env_id': 'BreakoutNoFrameskip-v4',
'exp_name': 'dqn_atari',
'exploration_fraction': 0.1,
'gamma': 0.99,
'hf_entity': '',
'learning_rate': 0.0001,
'learning_starts': 80000,
'save_model': True,
'seed': 1,
'start_e': 1,
'target_network_frequency': 1000,
'torch_deterministic': True,
'total_timesteps': 10000,
'track': False,
'train_frequency': 4,
'upload_model': True,
'wandb_entity': None,
'wandb_project_name': 'cleanRL'}
Evaluation results
- mean_reward on BreakoutNoFrameskip-v4self-reported2.70 +/- 4.12