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---
tags:
- BeamRiderNoFrameskip-v4
- deep-reinforcement-learning
- reinforcement-learning
- custom-implementation
library_name: cleanrl
model-index:
- name: DQN
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: BeamRiderNoFrameskip-v4
type: BeamRiderNoFrameskip-v4
metrics:
- type: mean_reward
value: 7155.60 +/- 2103.76
name: mean_reward
verified: false
---
# (CleanRL) **DQN** Agent Playing **BeamRiderNoFrameskip-v4**
This is a trained model of a DQN agent playing BeamRiderNoFrameskip-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/dqn_atari.py).
## Command to reproduce the training
```bash
curl -OL https://huggingface.co/cleanrl/BeamRiderNoFrameskip-v4-dqn_atari-seed1/raw/main/dqn.py
curl -OL https://huggingface.co/cleanrl/BeamRiderNoFrameskip-v4-dqn_atari-seed1/raw/main/pyproject.toml
curl -OL https://huggingface.co/cleanrl/BeamRiderNoFrameskip-v4-dqn_atari-seed1/raw/main/poetry.lock
poetry install --all-extras
python dqn_atari.py --track --capture-video --save-model --upload-model --hf-entity cleanrl --env-id BeamRiderNoFrameskip-v4 --seed 1
```
# Hyperparameters
```python
{'batch_size': 32,
'buffer_size': 1000000,
'capture_video': True,
'cuda': True,
'end_e': 0.01,
'env_id': 'BeamRiderNoFrameskip-v4',
'exp_name': 'dqn_atari',
'exploration_fraction': 0.1,
'gamma': 0.99,
'hf_entity': 'cleanrl',
'learning_rate': 0.0001,
'learning_starts': 80000,
'save_model': True,
'seed': 1,
'start_e': 1,
'target_network_frequency': 1000,
'torch_deterministic': True,
'total_timesteps': 10000000,
'track': True,
'train_frequency': 4,
'upload_model': True,
'wandb_entity': None,
'wandb_project_name': 'cleanRL'}
```
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