Push to Hub

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -98.41 +/- 86.57
+      value: 75.19 +/- 100.03
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
-{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__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 0x7afbf6fee3b0>", "_build": "<function DQNPolicy._build at 0x7afbf6fee440>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7afbf6fee4d0>", "forward": "<function DQNPolicy.forward at 0x7afbf6fee560>", "_predict": "<function DQNPolicy._predict at 0x7afbf6fee5f0>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7afbf6fee680>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7afbf6fee710>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7afbf6ffd1c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100000, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709542024243495470, "learning_rate": 0.0001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAIAaPj62DE4/Yh6Rvddvlbzu7g87+S8KOwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAPrTPj6bJ04/QPxhvdVwNb0pBgk7hp2MPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_episode_num": 195, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 24975, "buffer_size": 1000000, "batch_size": 32, "learning_starts": 100, "tau": 1.0, "gamma": 0.99, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", "__module__": "stable_baselines3.common.buffers", "__annotations__": "{'observations': <class 'numpy.ndarray'>, 'next_observations': <class 'numpy.ndarray'>, 'actions': <class 'numpy.ndarray'>, 'rewards': <class 'numpy.ndarray'>, 'dones': <class 'numpy.ndarray'>, 'timeouts': <class 'numpy.ndarray'>}", "__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 0x7afbf7113880>", "add": "<function ReplayBuffer.add at 0x7afbf7113910>", "sample": "<function ReplayBuffer.sample at 0x7afbf71139a0>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7afbf7113a30>", "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x7afbf7113ac0>)>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7afbf7117680>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.1, "exploration_fraction": 0.1, "target_update_interval": 250, "_n_calls": 100000, "max_grad_norm": 10, "exploration_rate": 0.1, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]", "high": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]", "low_repr": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]", "high_repr": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"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": "2.3.0a2", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__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 0x7d0f6db303a0>", "_build": "<function DQNPolicy._build at 0x7d0f6db30430>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7d0f6db304c0>", "forward": "<function DQNPolicy.forward at 0x7d0f6db30550>", "_predict": "<function DQNPolicy._predict at 0x7d0f6db305e0>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7d0f6db30670>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7d0f6db30700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d0f6db34500>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 100000, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709540420393297656, "learning_rate": 0.0001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAGZH8D0MfoQ+AoYWPnz6V74DCls8FDEjuwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAFpF7T0U7IY+VBgZPkIygb5MFF081ZW1ugAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_episode_num": 655, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 12500, "buffer_size": 1000000, "batch_size": 32, "learning_starts": 50000, "tau": 1.0, "gamma": 0.99, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", "__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 0x7d0f6db14820>", "add": "<function ReplayBuffer.add at 0x7d0f6db148b0>", "sample": "<function ReplayBuffer.sample at 0x7d0f6db14940>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7d0f6db149d0>", "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x7d0f6db14a60>)>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d0f6dc3b800>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.1, "exploration_fraction": 0.1, "target_update_interval": 250, "_n_calls": 100000, "max_grad_norm": 10, "exploration_rate": 0.1, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]", "high": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]", "low_repr": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]", "high_repr": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "batch_norm_stats": [], "batch_norm_stats_target": [], "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.133+-x86_64-with-glibc2.31 # 1 SMP Tue Dec 19 13:14:11 UTC 2023", "Python": "3.10.13", "Stable-Baselines3": "2.1.0", "PyTorch": "2.1.2+cpu", "GPU Enabled": "False", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.0", "OpenAI Gym": "0.26.2"}}

dqn-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:aa533751dd9de07bdc3db95bf9cc4f70ba74460672ea4b03928bb47c997682c3
-size 107126
+oid sha256:b821988625098a056b83b7c58e8b20f4e3d3f1039e37ac8fb87383047331176f
+size 106508

dqn-LunarLander-v2/_stable_baselines3_version

@@ -1 +1 @@
-2.3.0a2
+2.1.0

dqn-LunarLander-v2/data

@@ -5,15 +5,15 @@
         "__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 0x7afbf6fee3b0>",
-        "_build": "<function DQNPolicy._build at 0x7afbf6fee440>",
-        "make_q_net": "<function DQNPolicy.make_q_net at 0x7afbf6fee4d0>",
-        "forward": "<function DQNPolicy.forward at 0x7afbf6fee560>",
-        "_predict": "<function DQNPolicy._predict at 0x7afbf6fee5f0>",
-        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7afbf6fee680>",
-        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7afbf6fee710>",
+        "__init__": "<function DQNPolicy.__init__ at 0x7d0f6db303a0>",
+        "_build": "<function DQNPolicy._build at 0x7d0f6db30430>",
+        "make_q_net": "<function DQNPolicy.make_q_net at 0x7d0f6db304c0>",
+        "forward": "<function DQNPolicy.forward at 0x7d0f6db30550>",
+        "_predict": "<function DQNPolicy._predict at 0x7d0f6db305e0>",
+        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7d0f6db30670>",
+        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7d0f6db30700>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7afbf6ffd1c0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7d0f6db34500>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -22,12 +22,12 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1709542024243495470,
+    "start_time": 1709540420393297656,
     "learning_rate": 0.0001,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAIAaPj62DE4/Yh6Rvddvlbzu7g87+S8KOwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAGZH8D0MfoQ+AoYWPnz6V74DCls8FDEjuwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -35,25 +35,25 @@
     },
     "_last_original_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAPrTPj6bJ04/QPxhvdVwNb0pBgk7hp2MPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAFpF7T0U7IY+VBgZPkIygb5MFF081ZW1ugAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
     },
-    "_episode_num": 195,
+    "_episode_num": 655,
     "use_sde": false,
     "sde_sample_freq": -1,
     "_current_progress_remaining": 0.0,
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 24975,
+    "_n_updates": 12500,
     "buffer_size": 1000000,
     "batch_size": 32,
-    "learning_starts": 100,
+    "learning_starts": 50000,
     "tau": 1.0,
     "gamma": 0.99,
     "gradient_steps": 1,
@@ -62,15 +62,14 @@
         ":type:": "<class 'abc.ABCMeta'>",
         ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
         "__module__": "stable_baselines3.common.buffers",
-        "__annotations__": "{'observations': <class 'numpy.ndarray'>, 'next_observations': <class 'numpy.ndarray'>, 'actions': <class 'numpy.ndarray'>, 'rewards': <class 'numpy.ndarray'>, 'dones': <class 'numpy.ndarray'>, 'timeouts': <class 'numpy.ndarray'>}",
         "__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 0x7afbf7113880>",
-        "add": "<function ReplayBuffer.add at 0x7afbf7113910>",
-        "sample": "<function ReplayBuffer.sample at 0x7afbf71139a0>",
-        "_get_samples": "<function ReplayBuffer._get_samples at 0x7afbf7113a30>",
-        "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x7afbf7113ac0>)>",
+        "__init__": "<function ReplayBuffer.__init__ at 0x7d0f6db14820>",
+        "add": "<function ReplayBuffer.add at 0x7d0f6db148b0>",
+        "sample": "<function ReplayBuffer.sample at 0x7d0f6db14940>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7d0f6db149d0>",
+        "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x7d0f6db14a60>)>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7afbf7117680>"
+        "_abc_impl": "<_abc._abc_data object at 0x7d0f6dc3b800>"
     },
     "replay_buffer_kwargs": {},
     "train_freq": {
@@ -102,7 +101,7 @@
     },
     "action_space": {
         ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
-        ":serialized:": "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",
+        ":serialized:": "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",
         "n": "4",
         "start": "0",
         "_shape": [],
@@ -112,12 +111,12 @@
     "n_envs": 1,
     "lr_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "batch_norm_stats": [],
     "batch_norm_stats_target": [],
     "exploration_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     }
 }

dqn-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3f6ec6cd30af5bc4e6bc8bb6a9f6968454938e5f477d5dd479a66dec3a097946
-size 45408
+oid sha256:7bf959ac5391f26909a187f61e43fbf0cbb64621c546e88ff615342fa08a211e
+size 45216

dqn-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d24c69e8f5056018026a30f3a932f5d65043f6e3e1a217e17b127730c695050a
-size 44466
+oid sha256:6253a81777b16ae30e99659e5958d71cc9f418be4e1e5ad3cb9db41c40d0e611
+size 44338

dqn-LunarLander-v2/system_info.txt

@@ -1,9 +1,9 @@
-- 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: 2.3.0a2
-- PyTorch: 2.1.0+cu121
-- GPU Enabled: True
-- Numpy: 1.25.2
+- OS: Linux-5.15.133+-x86_64-with-glibc2.31 # 1 SMP Tue Dec 19 13:14:11 UTC 2023
+- Python: 3.10.13
+- Stable-Baselines3: 2.1.0
+- PyTorch: 2.1.2+cpu
+- GPU Enabled: False
+- Numpy: 1.26.4
 - Cloudpickle: 2.2.1
-- Gymnasium: 0.29.1
-- OpenAI Gym: 0.25.2
+- Gymnasium: 0.29.0
+- OpenAI Gym: 0.26.2

results.json

@@ -1 +1 @@
-{"mean_reward": -98.41357237061166, "std_reward": 86.56791224053667, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-04T08:54:38.656305"}
+{"mean_reward": 75.19120506179533, "std_reward": 100.03434697117845, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-04T08:54:45.710929"}