Upload DQN LunarLander-v2 trained agent

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DQN-LunarLander-v2.zip +3 -0
DQN-LunarLander-v2/_stable_baselines3_version +1 -0
DQN-LunarLander-v2/data +122 -0
DQN-LunarLander-v2/policy.optimizer.pth +3 -0
DQN-LunarLander-v2/policy.pth +3 -0
DQN-LunarLander-v2/pytorch_variables.pth +3 -0
DQN-LunarLander-v2/system_info.txt +7 -0
README.md +37 -0
config.json +1 -0
replay.mp4 +0 -0
results.json +1 -0

DQN-LunarLander-v2.zip ADDED Viewed

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DQN-LunarLander-v2/_stable_baselines3_version ADDED Viewed

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DQN-LunarLander-v2/data ADDED Viewed

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+        "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ",
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+        "make_q_net": "<function DQNPolicy.make_q_net at 0x7ff6cfb79940>",
+        "forward": "<function DQNPolicy.forward at 0x7ff6cfb799d0>",
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+        "bounded_above": "[False False False False False False False False]",
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+- OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.8.10
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.21.6
+- Gym: 0.21.0

README.md ADDED Viewed

	@@ -0,0 +1,37 @@

+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DQN
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 275.34 +/- 18.88
+      name: mean_reward
+      verified: false
+---
+# **DQN** Agent playing **LunarLander-v2**
+This is a trained model of a **DQN** agent playing **LunarLander-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
+...
+```

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Binary file (217 kB). View file

results.json ADDED Viewed

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