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ppo-LunarLander-v2-unit8
tanu20/ppo-LunarLander-v2-unit8
ppo-LunarLander-v2-unit8 is a reinforcement learning model from tanu20. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product.
PPO agent implemented from scratch using PyTorch for Unit 8 Part I of the Hugging Face Deep Reinforcement Learning Course.
Access
Public
Updated Sep 23, 2026
Repo size
277 KB
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Repo makeup
Click a slice to open those files.
.mp4234 KB · 83%
At a glance
- Task
- Reinforcement Learning
- Access
- Public
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026
- SHA
- 38617d02
Model card
From the Hugging Face model README
PPO LunarLander-v2
PPO agent implemented from scratch using PyTorch for Unit 8 Part I of the Hugging Face Deep Reinforcement Learning Course.
Evaluation
Mean reward: -132.37 +/- 43.43
Result used by the certification checker:
-175.80
Evaluation episodes: 10
Algorithm
- Proximal Policy Optimization (PPO)
- Actor-Critic
- Generalized Advantage Estimation (GAE)
- PPO clipped objective
- PyTorch
Environment
The original Unit 8 course uses LunarLander-v2.
The current Gymnasium release has deprecated v2 and provides
LunarLander-v3, so evaluation was performed with the current
compatible environment while preserving the course's required
LunarLander-v2 certification metadata.
Files
model.ptresults.jsonreplay.mp4
Course
Hugging Face Deep Reinforcement Learning Course Unit 8 Part I — PPO
- Task
- Reinforcement Learning
- Created
- Sep 23, 2026
- Updated
- Sep 23, 2026