Reinforcement Learning
stable-baselines3
CarRacing-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use clavierJupiter/car_racer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use clavierJupiter/car_racer with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="clavierJupiter/car_racer", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
initial commit
Browse files- .gitattributes +1 -0
- README.md +37 -0
- config.json +0 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +0 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +9 -0
- replay.mp4 +3 -0
- results.json +1 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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replay.mp4 filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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library_name: stable-baselines3
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tags:
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- CarRacing-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: CarRacing-v2
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type: CarRacing-v2
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metrics:
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- type: mean_reward
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value: 311.06 +/- 134.95
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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-v2**
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This is a trained model of a **PPO** agent playing **CarRacing-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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ppo-LunarLander-v2.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:6b3ee6cf25bd7854f06e5b6edbfb7171181189fad6f0e63ebc9c6b9dce0ef008
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size 26585758
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ppo-LunarLander-v2/_stable_baselines3_version
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2.0.0a5
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ppo-LunarLander-v2/data
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ppo-LunarLander-v2/policy.optimizer.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:699470db85de58f04563565b7026367a9e4f63b0089c0450bc866e19b6d39b52
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size 17416033
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ppo-LunarLander-v2/policy.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:d281891778381a1655259589ba0b7cc7b03aef35417fb32507bcf1347cf49481
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size 8710383
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ppo-LunarLander-v2/pytorch_variables.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
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size 864
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ppo-LunarLander-v2/system_info.txt
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- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
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- Python: 3.10.12
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- Stable-Baselines3: 2.0.0a5
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- PyTorch: 2.1.0+cu121
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- GPU Enabled: True
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- Numpy: 1.23.5
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- Cloudpickle: 2.2.1
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- Gymnasium: 0.28.1
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- OpenAI Gym: 0.25.2
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replay.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:c67e2a0c4edc5f02d59cf35e9da539db5cd4c6d63e1adb35020710e046922a52
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size 1162916
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results.json
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{"mean_reward": 311.0585479, "std_reward": 134.94585075885882, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-01-15T23:29:27.685230"}
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