Upload PPO CarRacing-v0 trained agent
Browse files- README.md +37 -0
- config.json +0 -0
- ppo-CarRacing-v0.zip +3 -0
- ppo-CarRacing-v0/_stable_baselines3_version +1 -0
- ppo-CarRacing-v0/data +0 -0
- ppo-CarRacing-v0/policy.optimizer.pth +3 -0
- ppo-CarRacing-v0/policy.pth +3 -0
- ppo-CarRacing-v0/pytorch_variables.pth +3 -0
- ppo-CarRacing-v0/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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- CarRacing-v0
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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: CarRacing-v0
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type: CarRacing-v0
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metrics:
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- type: mean_reward
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value: 102.82 +/- 53.96
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name: mean_reward
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verified: false
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---
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# **PPO** Agent playing **CarRacing-v0**
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This is a trained model of a **PPO** agent playing **CarRacing-v0**
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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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ppo-CarRacing-v0.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:11b70755c8921dd576f4d92f77a3335dc8a307930f5a1c3125a09be0f1aefe93
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size 43340268
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ppo-CarRacing-v0/_stable_baselines3_version
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1.6.2
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ppo-CarRacing-v0/data
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ppo-CarRacing-v0/policy.optimizer.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:2533a5c4e990bb21b0e6b138f6b03413483e817ce8472722c87d7cab14859123
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size 28391536
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ppo-CarRacing-v0/policy.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:d0ece2c5fc62dd15c46cd562ef2d75a320d921400e07ed661dbba852acde7902
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size 14194942
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ppo-CarRacing-v0/pytorch_variables.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
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size 431
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ppo-CarRacing-v0/system_info.txt
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OS: Linux-5.10.147+-x86_64-with-glibc2.27 #1 SMP Sat Dec 10 16:00:40 UTC 2022
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Python: 3.8.16
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Stable-Baselines3: 1.6.2
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PyTorch: 1.13.0+cu116
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GPU Enabled: True
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Numpy: 1.21.6
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Gym: 0.21.0
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replay.mp4
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Binary file (585 kB). View file
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results.json
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{"mean_reward": 102.82458411306143, "std_reward": 53.964141655292224, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-10T12:41:32.080951"}
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