Reinforcement Learning
stable-baselines3
CarRacing-v0
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use kostasang/ppo-CarRacing-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use kostasang/ppo-CarRacing-v0 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="kostasang/ppo-CarRacing-v0", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Upload ppo model
Browse files- README.md +1 -1
- config.json +0 -0
- ppo-CarRacing-v0.zip +2 -2
- ppo-CarRacing-v0/data +0 -0
- ppo-CarRacing-v0/policy.optimizer.pth +1 -1
- ppo-CarRacing-v0/policy.pth +1 -1
- replay.mp4 +2 -2
- results.json +1 -1
README.md
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type: CarRacing-v0
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metrics:
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- type: mean_reward
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value:
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name: mean_reward
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verified: false
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---
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type: CarRacing-v0
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metrics:
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- type: mean_reward
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value: 652.88 +/- 132.70
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name: mean_reward
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verified: false
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---
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config.json
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ppo-CarRacing-v0.zip
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ppo-CarRacing-v0/data
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ppo-CarRacing-v0/policy.optimizer.pth
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ppo-CarRacing-v0/policy.pth
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replay.mp4
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results.json
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{"mean_reward":
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{"mean_reward": 652.8770271234214, "std_reward": 132.70437837564373, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-30T14:46:54.638751"}
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