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DQN-LunarLander-v2-version2
GZHUFB/DQN-LunarLander-v2-version2
DQN-LunarLander-v2-version2 is a reinforcement learning model from GZHUFB. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for stable-baselines3.
This is a trained model of a DQN agent playing LunarLander-v2 using the stable-baselines3 library.
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At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Access
- Public
- Created
- Dec 12, 2023
- Updated
- Dec 12, 2023
- SHA
- 249fd763
Model card
From the Hugging Face model README
DQN Agent playing LunarLander-v2
This is a trained model of a DQN agent playing LunarLander-v2 using the stable-baselines3 library.
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
#The hyper-parameter
model = DQN(
"MlpPolicy",
env=env,
buffer_size=100000,
learning_starts=50000,
batch_size=128,
train_freq=1,
gradient_steps=3,
tau=1.0,
gamma=0.99,
learning_rate=0.0001,
target_update_interval=10000,
exploration_initial_eps=1.0,
exploration_fraction=0.1,
exploration_final_eps=0.05,
policy_kwargs=dict(net_arch=[256, 256]),
device='auto',
verbose=1
)
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- Dec 12, 2023
- Updated
- Dec 12, 2023