optimized hyperparameters (optuna) trained locally on A4000, adam

README.md

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+---
+library_name: stable-baselines3
+tags:
+- PandaReachDense-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PandaReachDense-v2
+      type: PandaReachDense-v2
+    metrics:
+    - type: mean_reward
+      value: -0.58 +/- 0.29
+      name: mean_reward
+      verified: false
+---
+
+# **A2C** Agent playing **PandaReachDense-v2**
+This is a trained model of a **A2C** agent playing **PandaReachDense-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

a2c-PandaReachDense-v2.zip

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a2c-PandaReachDense-v2/_stable_baselines3_version

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+1.8.0a13

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a2c-PandaReachDense-v2/policy.optimizer.pth

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a2c-PandaReachDense-v2/policy.pth

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a2c-PandaReachDense-v2/pytorch_variables.pth

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a2c-PandaReachDense-v2/system_info.txt

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+- OS: Linux-5.14.0-239.el9.x86_64-x86_64-with-glibc2.34 # 1 SMP PREEMPT_DYNAMIC Thu Jan 19 14:14:19 UTC 2023
+- Python: 3.9.16
+- Stable-Baselines3: 1.8.0a13
+- PyTorch: 2.0.0+cu117
+- GPU Enabled: True
+- Numpy: 1.21.2
+- Gym: 0.21.0

config.json

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results.json

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