Instructions to use Mzou000/PPO-Ant-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Mzou000/PPO-Ant-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Mzou000/PPO-Ant-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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license: mit
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---
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license: mit
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tags:
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- reinforcement-learning
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- stable-baselines3
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- mujoco
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- ant-v4
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- ppo
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pipeline_tag: reinforcement-learning
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library_name: stable-baselines3
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model_name: PPO-Ant-v4
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---
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# PPO - Ant-v4 🌟
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A Proximal Policy Optimization (PPO) agent trained with **stable-baselines3** on the MuJoCo **`Ant-v4`** environment.
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| | Details |
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|---|---|
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| Environment | `gymnasium==0.29` & `mujoco==2.3` (`Ant-v4`) |
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| Algorithm | PPO (`stable-baselines3==2.3.0`) |
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| Timesteps | **100 000** |
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| Policy | `MlpPolicy` *(2 × 64 hidden, tanh)* |
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| Return (mean ± std) | ~ *964* |
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| Seed | `0` |
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## Hyper-parameters
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```jsonc
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{
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"n_steps": 128,
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"batch_size": 64,
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"n_epochs": 20,
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"gamma": 0.99,
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"learning_rate": 3e-4,
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"ent_coef": 0.0,
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"clip_range": 0.2
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}
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