metadata
library_name: stable-baselines3
tags:
- LunarLander-v2
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: >-
PPO with MlpPolicy setting - verbose=1, n_steps=1024, batch_size=64,
n_epochs = 4, gamma = 0.999, gae_lambda = 0.98, ent_coef = 0.01
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: LunarLander-v2
type: LunarLander-v2
metrics:
- type: mean_reward
value: 271.13 +/- 22.25
name: mean_reward
verified: false
PPO with MlpPolicy setting - verbose=1, n_steps=1024, batch_size=64, n_epochs = 4, gamma = 0.999, gae_lambda = 0.98, ent_coef = 0.01 Agent playing LunarLander-v2
This is a trained model of a PPO with MlpPolicy setting - verbose=1, n_steps=1024, batch_size=64, n_epochs = 4, gamma = 0.999, gae_lambda = 0.98, ent_coef = 0.01 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
...