README.md

metadata

license: mit
tags:
  - reinforcement-learning
  - ppo
  - gymnasium
  - deep-rl-course
  - LunarLander-v2
model-index:
  - name: PPO LunarLander-v3
    results:
      - task:
          type: reinforcement-learning
          name: Reinforcement Learning
        dataset:
          name: LunarLander-v3
          type: LunarLander-v3
        metrics:
          - type: mean_reward
            value: -229.885
            name: Mean Reward

PPO from scratch — LunarLander-v3

Trained using a CleanRL-style PyTorch PPO implementation adapted for Gymnasium.

Evaluation over 10 episodes: -229.89 ± 22.10.

• model.pt: actor-critic PyTorch state dict
• ppo.py: full training/evaluation/upload source
• replay.mp4: evaluation video (if rendering succeeded)
• hyperparameters.json: training settings
• eval_results.json: evaluation results

To run locally, install PyTorch, gymnasium[box2d], imageio, imageio-ffmpeg, tensorboard, and huggingface_hub.