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README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 40.65 +/- 103.04
+      value: 109.12 +/- 18.64
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
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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 0x7fcbcc9b4ca0>", "_build": "<function DQNPolicy._build at 0x7fcbcc9b4d30>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7fcbcc9b4dc0>", "forward": "<function DQNPolicy.forward at 0x7fcbcc9b4e50>", "_predict": "<function DQNPolicy._predict at 0x7fcbcc9b4ee0>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7fcbcc9b4f70>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7fcbcc9b5000>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fcbcc9b1440>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100000, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1688626326065901139, 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dqn-LunarLander-v2.zip

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dqn-LunarLander-v2/data

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         "__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    ",
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         "__abstractmethods__": "frozenset()",
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     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
@@ -63,12 +63,12 @@
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         "__module__": "stable_baselines3.common.buffers",
         "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
-        "__init__": "<function ReplayBuffer.__init__ at 0x7fcbcc985120>",
-        "add": "<function ReplayBuffer.add at 0x7fcbcc9851b0>",
-        "sample": "<function ReplayBuffer.sample at 0x7fcbcc985240>",
-        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fcbcc9852d0>",
+        "__init__": "<function ReplayBuffer.__init__ at 0x7f5c60fbbd00>",
+        "add": "<function ReplayBuffer.add at 0x7f5c60fbbd90>",
+        "sample": "<function ReplayBuffer.sample at 0x7f5c60fbbe20>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7f5c60fbbeb0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fcbcc97f080>"
+        "_abc_impl": "<_abc._abc_data object at 0x7f5c60fc2ac0>"
     },
     "replay_buffer_kwargs": {},
     "train_freq": {
@@ -100,7 +100,7 @@
     },
     "action_space": {
         ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
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         "n": "4",
         "start": "0",
         "_shape": [],
@@ -110,12 +110,12 @@
     "n_envs": 1,
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+size 44783

dqn-LunarLander-v2/policy.pth

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dqn-LunarLander-v2/system_info.txt

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-- OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
+- OS: Linux-5.15.90.1-microsoft-standard-WSL2-x86_64-with-glibc2.35 # 1 SMP Fri Jan 27 02:56:13 UTC 2023
 - Python: 3.10.12
 - Stable-Baselines3: 2.0.0
-- PyTorch: 2.0.1+cu118
-- GPU Enabled: True
-- Numpy: 1.22.4
+- PyTorch: 2.0.1+cu117
+- GPU Enabled: False
+- Numpy: 1.25.0
 - Cloudpickle: 2.2.1
 - Gymnasium: 0.28.1
-- OpenAI Gym: 0.25.2
+- OpenAI Gym: 0.26.2

results.json

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