Upload DQN MountainCar-v0 trained agent

DQN_Mountain.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8bae38abf95d4a9ec1d94819a550b4645fc16a3fbf0656d48ff395697e923ec2
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DQN_Mountain/_stable_baselines3_version

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+2.0.0a5

DQN_Mountain/data

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+    }
+}

DQN_Mountain/policy.optimizer.pth

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DQN_Mountain/policy.pth

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DQN_Mountain/pytorch_variables.pth

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DQN_Mountain/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
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.1.0+cu121
+- GPU Enabled: False
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

README.md

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+---
+library_name: stable-baselines3
+tags:
+- MountainCar-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DQN
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: MountainCar-v0
+      type: MountainCar-v0
+    metrics:
+    - type: mean_reward
+      value: -111.80 +/- 17.71
+      name: mean_reward
+      verified: false
+---
+
+# **DQN** Agent playing **MountainCar-v0**
+This is a trained model of a **DQN** agent playing **MountainCar-v0**
+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
+
+...
+```

config.json

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results.json

@@ -0,0 +1 @@
+{"mean_reward": -111.8, "std_reward": 17.713271860387625, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-21T03:31:26.073267"}