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PPO-LunarLander-v2-Unit8
herurg/PPO-LunarLander-v2-Unit8
PPO-LunarLander-v2-Unit8 is a reinforcement learning model from herurg. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product.
This is a PPO agent trained for Hugging Face Deep RL Course Unit 8 Part I.
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At a glance
- Task
- Reinforcement Learning
- Access
- Public
- Created
- Aug 23, 2026
- Updated
- Aug 23, 2026
- SHA
- 0be1f384
Model card
From the Hugging Face model README
PPO Agent Playing LunarLander-v2
This is a PPO agent trained for Hugging Face Deep RL Course Unit 8 Part I.
The PPO implementation follows the CleanRL-style architecture and was adapted to Gymnasium.
Evaluation
- Mean reward: -106.451102
- Standard deviation: 72.517478
- Lower-bound score: -178.968580
- Evaluation episodes: 10
Training
- Environment: LunarLander-v2
- Algorithm: PPO
- Training timesteps: 51,200
- Framework: PyTorch
- Environment API: Gymnasium
- Task
- Reinforcement Learning
- Created
- Aug 23, 2026
- Updated
- Aug 23, 2026