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DQN-FlappyBird-v0.zip +3 -0
DQN-FlappyBird-v0/_stable_baselines3_version +1 -0
DQN-FlappyBird-v0/data +122 -0
DQN-FlappyBird-v0/policy.optimizer.pth +3 -0
DQN-FlappyBird-v0/policy.pth +3 -0
DQN-FlappyBird-v0/pytorch_variables.pth +3 -0
DQN-FlappyBird-v0/system_info.txt +9 -0
README.md +37 -0
config.json +1 -0
replay.mp4 +0 -0
results.json +1 -0

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DQN-FlappyBird-v0/_stable_baselines3_version ADDED Viewed

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1	+ 2.1.0

DQN-FlappyBird-v0/data ADDED Viewed

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+{
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+        "__module__": "stable_baselines3.dqn.policies",
+        "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}",
+        "__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    ",
+        "__init__": "<function DQNPolicy.__init__ at 0x32d77f9d0>",
+        "_build": "<function DQNPolicy._build at 0x32d77fa60>",
+        "make_q_net": "<function DQNPolicy.make_q_net at 0x32d77faf0>",
+        "forward": "<function DQNPolicy.forward at 0x32d77fb80>",
+        "_predict": "<function DQNPolicy._predict at 0x32d77fc10>",
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+        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x32d77fd30>",
+        "__abstractmethods__": "frozenset()",
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+    }
+}

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+size 864

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	@@ -0,0 +1,9 @@

+- OS: macOS-14.4.1-arm64-arm-64bit Darwin Kernel Version 23.4.0: Fri Mar 15 00:12:41 PDT 2024; root:xnu-10063.101.17~1/RELEASE_ARM64_T8103
+- Python: 3.9.19
+- Stable-Baselines3: 2.1.0
+- PyTorch: 2.2.1
+- GPU Enabled: False
+- Numpy: 1.26.4
+- Cloudpickle: 3.0.0
+- Gymnasium: 0.29.1
+- OpenAI Gym: 0.26.2

README.md ADDED Viewed

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

+---
+library_name: stable-baselines3
+tags:
+- FlappyBird-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DQN
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: FlappyBird-v0
+      type: FlappyBird-v0
+    metrics:
+    - type: mean_reward
+      value: -9.30 +/- 0.00
+      name: mean_reward
+      verified: false
+---
+# **DQN** Agent playing **FlappyBird-v0**
+This is a trained model of a **DQN** agent playing **FlappyBird-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
+...
+```

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``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function DQNPolicy.__init__ at 0x32d77f9d0>", "_build": "<function DQNPolicy._build at 0x32d77fa60>", "make_q_net": "<function DQNPolicy.make_q_net at 0x32d77faf0>", "forward": "<function DQNPolicy.forward at 0x32d77fb80>", "_predict": "<function DQNPolicy._predict at 0x32d77fc10>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x32d77fca0>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x32d77fd30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x32d788540>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2000, "_total_timesteps": 2000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713697931718345000, "learning_rate": 0.0001, "tensorboard_log": null, "_last_obs": {":type:": "<class 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