Upload PPO LunarLander-v2 trained agent (Lunar)
Browse files- README.md +37 -0
- config.json +1 -0
- ppo-LunarLander-v2-Lunar100K.zip +3 -0
- ppo-LunarLander-v2-Lunar100K/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2-Lunar100K/data +98 -0
- ppo-LunarLander-v2-Lunar100K/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2-Lunar100K/policy.pth +3 -0
- ppo-LunarLander-v2-Lunar100K/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2-Lunar100K/system_info.txt +7 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
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---
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library_name: stable-baselines3
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tags:
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- LunarLander-v2
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- deep-reinforcement-learning
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- reinforcement-learning
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- stable-baselines3
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model-index:
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- name: PPO
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results:
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- task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: LunarLander-v2
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type: LunarLander-v2
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metrics:
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- type: mean_reward
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value: -142.12 +/- 60.88
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name: mean_reward
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verified: false
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---
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# **PPO** Agent playing **LunarLander-v2**
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This is a trained model of a **PPO** agent playing **LunarLander-v2**
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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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## Usage (with Stable-baselines3)
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TODO: Add your code
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```python
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from stable_baselines3 import ...
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from huggingface_sb3 import load_from_hub
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...
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```
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config.json
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