Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 237.41 +/- 60.98
+      value: 254.27 +/- 17.91
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
-{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 ActorCriticPolicy.__init__ at 0x7ff296707b80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff296707c10>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff296707ca0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff296707d30>", "_build": "<function ActorCriticPolicy._build at 0x7ff296707dc0>", "forward": "<function ActorCriticPolicy.forward at 0x7ff296707e50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff296707ee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff296707f70>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff296709040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff2967090d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff296709160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff2967091f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff2967862a0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1675518619083698362, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"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"}}
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 ActorCriticPolicy.__init__ at 0x7f3b3bd87a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3b3bd87af0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3b3bd87b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3b3bd87c10>", "_build": "<function ActorCriticPolicy._build at 0x7f3b3bd87ca0>", "forward": "<function ActorCriticPolicy.forward at 0x7f3b3bd87d30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3b3bd87dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3b3bd87e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3b3bd87ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3b3bd87f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3b3bd8b040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3b3bd8b0d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f3bec0a9840>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1678283889199125285, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM3gFjxIj6y629IEtW8U968T3aa46HViNAAAgD8AAIA/msnbun/NcT63WQQ+5Timvi4Yqj1GSPM8AAAAAAAAAAAAuJe9MSojP/oaZT3r3rq+MXHRuzrFYT0AAAAAAAAAAAB3FL1c9266ToAIufJvPrazRwi7wP8gOAAAgD8AAIA/La8yvvj7VD9G63C7Q7DfvpDkyr1mzlk9AAAAAAAAAADat9u9sv6CP3liRL4BwtW+X5nYvZM5d7wAAAAAAAAAAJrvhDwVpVc++97xPJVsa75ZHfI8JtFGvQAAAAAAAAAAZgpQvLbyMryHdoS7vKRZPKcdmr3vgjY9AACAPwAAgD+zgHe9KfCiP8a14L7+p9a+31szvUDrMr4AAAAAAAAAAMBDHD6FJ/m72G5kPAbjpLpDW3O9nguKuwAAgD8AAIA/gICIPecAEz5wd8W9YsCqvo5gnr3YzRs8AAAAAAAAAACa68M81yB+PAAz6b3qfB2+g6RzvUWzpr0AAAAAAAAAAAAsPbzvook/742SvTB/sL4iTQC9X0qVPQAAAAAAAAAA2m+xPSR53D22lJq82+Kmvnz1xLsmiji7AAAAAAAAAAANhGw+PHruPhP+jr4wsKK+Rq89vJr06r0AAAAAAAAAAJBAsT61X2Y/ygXpPbXeq76VR5U+zfuRvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"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": "1.22.4", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6273b73600d34c404f63bccaaf41469031a025f4f404729e63b9e140dcaf57c4
-size 147178
+oid sha256:c593f361d10c908153dd310312004d62f96d39939d223843313375c1d730469b
+size 147408

ppo-LunarLander-v2/_stable_baselines3_version

@@ -1 +1 @@
-1.6.2
+1.7.0

ppo-LunarLander-v2/data

@@ -3,20 +3,21 @@
         ":type:": "<class 'abc.ABCMeta'>",
         ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
         "__module__": "stable_baselines3.common.policies",
-        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\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 ActorCriticPolicy.__init__ at 0x7fab2fd47040>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fab2fd470d0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fab2fd47160>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fab2fd471f0>",
-        "_build": "<function ActorCriticPolicy._build at 0x7fab2fd47280>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7fab2fd47310>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fab2fd473a0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7fab2fd47430>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fab2fd474c0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fab2fd47550>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fab2fd475e0>",
+        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 ActorCriticPolicy.__init__ at 0x7f3b3bd87a60>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3b3bd87af0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3b3bd87b80>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3b3bd87c10>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f3b3bd87ca0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f3b3bd87d30>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3b3bd87dc0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3b3bd87e50>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f3b3bd87ee0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3b3bd87f70>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3b3bd8b040>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3b3bd8b0d0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7fab2fd41480>"
+        "_abc_impl": "<_abc_data object at 0x7f3bec0a9840>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -42,21 +43,21 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 1212416,
-    "_total_timesteps": 1200000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1673351846095566214,
+    "start_time": 1678283889199125285,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,16 +67,16 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.010346666666666726,
+    "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "gAWVYhAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIu5hmuteQcECUhpRSlIwBbJRL6owBdJRHQKJBbrftQbd1fZQoaAZoCWgPQwhsByP2CU1uQJSGlFKUaBVL6mgWR0CiQdYKpkwwdX2UKGgGaAloD0MI0sPQ6qQic0CUhpRSlGgVS/5oFkdAokKYnndO7HV9lChoBmgJaA9DCGhdo+VApHBAlIaUUpRoFUvaaBZHQKJCoRXfZVZ1fZQoaAZoCWgPQwjAJQD/1ORwQJSGlFKUaBVNJAFoFkdAokNh+H8CP3V9lChoBmgJaA9DCMQLIlKT9HJAlIaUUpRoFU0AAWgWR0CiQ4k61b7kdX2UKGgGaAloD0MI7rQ1Ihi2cUCUhpRSlGgVTQgBaBZHQKJDq+De0ol1fZQoaAZoCWgPQwjDgZAsYO9xQJSGlFKUaBVNOgFoFkdAokOyfzz3AXV9lChoBmgJaA9DCKSLTSsFu29AlIaUUpRoFU0GAWgWR0CiQ74SYgJUdX2UKGgGaAloD0MIBoGVQ0tKcECUhpRSlGgVTTkBaBZHQKJEBOfNA1N1fZQoaAZoCWgPQwhGeHsQgkBvQJSGlFKUaBVNOgFoFkdAokQiz3RG+nV9lChoBmgJaA9DCCxkrgzqRHJAlIaUUpRoFU0NAWgWR0CiRG6vJRwZdX2UKGgGaAloD0MI2IFzRtQzcUCUhpRSlGgVTS4BaBZHQKJEskmhM8J1fZQoaAZoCWgPQwhzSGqh5C1wQJSGlFKUaBVNBAFoFkdAokTvMyJsPHV9lChoBmgJaA9DCLWkoxyMfHFAlIaUUpRoFUv/aBZHQKJE+bfgrH51fZQoaAZoCWgPQwjDZ+vgoC1zQJSGlFKUaBVL+2gWR0CiRVH9NvfkdX2UKGgGaAloD0MIKV5lbRM4cUCUhpRSlGgVTSQBaBZHQKJFV4NZvDR1fZQoaAZoCWgPQwgIdZFCWUZvQJSGlFKUaBVL9mgWR0CiReqLCN0edX2UKGgGaAloD0MIih9j7hpDcUCUhpRSlGgVTQQBaBZHQKJGJIBBAwB1fZQoaAZoCWgPQwglH7sLFIpxQJSGlFKUaBVL+GgWR0CiRtZgw482dX2UKGgGaAloD0MIEM8SZISkb0CUhpRSlGgVTRMBaBZHQKJHInF5v991fZQoaAZoCWgPQwjJrx9iAzNwQJSGlFKUaBVNHgFoFkdAokes4vN/v3V9lChoBmgJaA9DCBJPdjMjeXJAlIaUUpRoFU0kAWgWR0CiR7d2Pkq+dX2UKGgGaAloD0MIyGEwf8VDcUCUhpRSlGgVTQYBaBZHQKJHvmozeoF1fZQoaAZoCWgPQwjieD4DKmVwQJSGlFKUaBVNNwFoFkdAokf4mZ3LWHV9lChoBmgJaA9DCD83NGXn+3JAlIaUUpRoFU0gAWgWR0CiR//I8yN5dX2UKGgGaAloD0MI7BaBsT6KckCUhpRSlGgVTQMBaBZHQKJIDX18LKF1fZQoaAZoCWgPQwhwehfvRzhuQJSGlFKUaBVL9GgWR0CiSF8eKbazdX2UKGgGaAloD0MITaJe8Cl0ckCUhpRSlGgVTSEBaBZHQKJIudpZfUp1fZQoaAZoCWgPQwg3pbxWgn9wQJSGlFKUaBVNEAFoFkdAokjLTpgTiHV9lChoBmgJaA9DCMx5xr5k/mdAlIaUUpRoFU2BAmgWR0CiSQWv0RODdX2UKGgGaAloD0MIHH433XJmckCUhpRSlGgVTQ0BaBZHQKJJGbhFVkt1fZQoaAZoCWgPQwgnpaDbi/FyQJSGlFKUaBVNFgFoFkdAokk2bsniN3V9lChoBmgJaA9DCNiDSfFxYXBAlIaUUpRoFU0NAWgWR0CiSaySFGoadX2UKGgGaAloD0MIL1G9NXB0cUCUhpRSlGgVTQsBaBZHQKJKlaEBbOh1fZQoaAZoCWgPQwhZ+zvbo2RxQJSGlFKUaBVL/GgWR0CiSqJcgQpXdX2UKGgGaAloD0MIQu4iTJFIckCUhpRSlGgVS+BoFkdAokq6sEJSi3V9lChoBmgJaA9DCMSVs3dGxHBAlIaUUpRoFU1IAWgWR0CiStLS3LFGdX2UKGgGaAloD0MICCEgX0JEcUCUhpRSlGgVS/BoFkdAoktBgE2YOXV9lChoBmgJaA9DCJcd4h+2vm1AlIaUUpRoFUv6aBZHQKJLeE1VHWl1fZQoaAZoCWgPQwhvSKMCp3BxQJSGlFKUaBVNGwFoFkdAokujeGfwqnV9lChoBmgJaA9DCEewcf07B3BAlIaUUpRoFU0eAWgWR0CiS6gxrSE2dX2UKGgGaAloD0MI5zi3CXdQcUCUhpRSlGgVTRoBaBZHQKJL0YJE6T51fZQoaAZoCWgPQwhgAUwZOEQxQJSGlFKUaBVLy2gWR0CiS9dpAUtadX2UKGgGaAloD0MIn+OjxVkockCUhpRSlGgVTTkBaBZHQKJV5QEZBLR1fZQoaAZoCWgPQwgbDeAtkCVyQJSGlFKUaBVNBgFoFkdAolYcrZrYXnV9lChoBmgJaA9DCLE1W3nJTW9AlIaUUpRoFU0/AWgWR0CiVlXAEdNndX2UKGgGaAloD0MIutdJfdnEckCUhpRSlGgVTUsBaBZHQKJWmaFVT751fZQoaAZoCWgPQwitodRexIRuQJSGlFKUaBVNEwFoFkdAolbU0WM0g3V9lChoBmgJaA9DCCR9WkX/F3NAlIaUUpRoFU1LAWgWR0CiVu9Gy5ZsdX2UKGgGaAloD0MII7pnXSMpbkCUhpRSlGgVS/FoFkdAolcx0IToMnV9lChoBmgJaA9DCBKgppatS25AlIaUUpRoFUvwaBZHQKJXWMrmQsB1fZQoaAZoCWgPQwh3gv3X+XZzQJSGlFKUaBVLxmgWR0CiV4i6QNkOdX2UKGgGaAloD0MIe6NWmD4HcUCUhpRSlGgVTTABaBZHQKJX/cVxjrl1fZQoaAZoCWgPQwjVWpiFNhxwQJSGlFKUaBVL6mgWR0CiWD5mI0qIdX2UKGgGaAloD0MI0o2wqAiPcUCUhpRSlGgVTRMBaBZHQKJYb2exwAF1fZQoaAZoCWgPQwiPjUC8blVwQJSGlFKUaBVNJAFoFkdAolh59kSVW3V9lChoBmgJaA9DCF4td2bCWXJAlIaUUpRoFU1lAWgWR0CiWNIuXeFddX2UKGgGaAloD0MIJGJKJFG0ckCUhpRSlGgVTTwBaBZHQKJZKvV3EAJ1fZQoaAZoCWgPQwjBx2DFKWNuQJSGlFKUaBVNFQFoFkdAolmpsfq5b3V9lChoBmgJaA9DCBxBKsUOfHJAlIaUUpRoFU1YAWgWR0CiWb5Yoy9FdX2UKGgGaAloD0MIBhIUP0brcUCUhpRSlGgVTRoBaBZHQKJZ+Y3Ns311fZQoaAZoCWgPQwjRIXAkUDxwQJSGlFKUaBVNAAFoFkdAoloRJVbRnnV9lChoBmgJaA9DCCAJ+3bS3XJAlIaUUpRoFUvhaBZHQKJaQBRyfcx1fZQoaAZoCWgPQwgqq+l64n1yQJSGlFKUaBVNKQFoFkdAolpdaIN3GHV9lChoBmgJaA9DCOYIGcizUHJAlIaUUpRoFU0KAWgWR0CiWwKO938odX2UKGgGaAloD0MIgXhdv6AbcUCUhpRSlGgVTQIBaBZHQKJbJBeokzJ1fZQoaAZoCWgPQwjexmZH6iVxQJSGlFKUaBVNNQFoFkdAols01Q66rnV9lChoBmgJaA9DCG9JDthVT3FAlIaUUpRoFUv5aBZHQKJbzOMVDa51fZQoaAZoCWgPQwiwjA3d7HtxQJSGlFKUaBVNbAFoFkdAolvqJ0nw5XV9lChoBmgJaA9DCFXa4hqfQXBAlIaUUpRoFU0AAWgWR0CiXCDklu3udX2UKGgGaAloD0MIkfC9v4ElckCUhpRSlGgVTQ0BaBZHQKJcQ3VCojx1fZQoaAZoCWgPQwi5wVCH1YByQJSGlFKUaBVNPwFoFkdAolx+xD9fkXV9lChoBmgJaA9DCH+IDRbOy29AlIaUUpRoFU0PAWgWR0CiXKwSrYGudX2UKGgGaAloD0MILWACty7dckCUhpRSlGgVTSMBaBZHQKJdTj0cwQF1fZQoaAZoCWgPQwhR+kLIOaByQJSGlFKUaBVL62gWR0CiXVNjCpFTdX2UKGgGaAloD0MICaUvhFx5cECUhpRSlGgVTRIBaBZHQKJdj2Qnx8V1fZQoaAZoCWgPQwitMeiE0DFxQJSGlFKUaBVL+mgWR0CiXZ4KYzBRdX2UKGgGaAloD0MIDwu1pvkOc0CUhpRSlGgVS/1oFkdAol335BTn73V9lChoBmgJaA9DCNnqckrAgHJAlIaUUpRoFU01AWgWR0CiXhuDzyz5dX2UKGgGaAloD0MImuleJ3UpckCUhpRSlGgVTRQBaBZHQKJeLCHh0hh1fZQoaAZoCWgPQwjXoC+9fb9uQJSGlFKUaBVNLQFoFkdAol88fms/6nV9lChoBmgJaA9DCKnYmNcRYXJAlIaUUpRoFUv4aBZHQKJfUEpRXOp1fZQoaAZoCWgPQwjeA3RfzkxxQJSGlFKUaBVNMgFoFkdAol9rHbRF7XV9lChoBmgJaA9DCInPnWD/vUhAlIaUUpRoFUvUaBZHQKJfbmnO0LN1fZQoaAZoCWgPQwjLETKQJzFxQJSGlFKUaBVNNwFoFkdAol+I44p+dHV9lChoBmgJaA9DCIwRiUILNHBAlIaUUpRoFU0qAWgWR0CiX+NxlxwRdX2UKGgGaAloD0MIxsGlY85ucECUhpRSlGgVTSoBaBZHQKJgOhf0Eox1fZQoaAZoCWgPQwiOd0fGatcxQJSGlFKUaBVL1WgWR0CiYEGuTzNEdX2UKGgGaAloD0MI2JqtvGSOckCUhpRSlGgVTTIBaBZHQKJgeYbbUPR1fZQoaAZoCWgPQwgz4Zf6+cFvQJSGlFKUaBVNJgFoFkdAomC6fapPynV9lChoBmgJaA9DCB9JSQ+DsXBAlIaUUpRoFUv2aBZHQKJg7QVKwpx1fZQoaAZoCWgPQwhwsg3cARJuQJSGlFKUaBVNCwFoFkdAomDz1VYISnV9lChoBmgJaA9DCNJRDmaTXnNAlIaUUpRoFUvqaBZHQKJhUCo0hvB1fZQoaAZoCWgPQwghPrDjP0ZxQJSGlFKUaBVNBQFoFkdAomG8ofCAMHV9lChoBmgJaA9DCBRZayg1eXFAlIaUUpRoFU0uAWgWR0CiYh7qQiiZdX2UKGgGaAloD0MIraOqCaJ7b0CUhpRSlGgVTUgBaBZHQKJiHbj94u91fZQoaAZoCWgPQwjLLEKxledwQJSGlFKUaBVL72gWR0CiYqzJZGKAdX2UKGgGaAloD0MIAySaQFEWcUCUhpRSlGgVS/JoFkdAomK7AnDziHV9lChoBmgJaA9DCBhEpKZds3BAlIaUUpRoFUv+aBZHQKJjATWXkYJ1ZS4="
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 324,
+    "_n_updates": 248,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,
@@ -86,7 +87,7 @@
     "n_epochs": 4,
     "clip_range": {
         ":type:": "<class 'function'>",
-        ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
+        ":serialized:": "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"
     },
     "clip_range_vf": null,
     "normalize_advantage": true,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f07da42c7a16ab51684cf7eb6f8c17d01a08d9f3823e072dccb1aca175684f6b
+oid sha256:ca30bec5db00462eac5e9447e3452e21fe13e39be888693e0dfdf05ce8c8c64f
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4a58cc55683a640a71b1f3f48c5823aaf069073fa3d1c1bada1ba871fec906d5
-size 43201
+oid sha256:f1dba764e1604fe62e1c59d5664ce9de9746ad9c78b0221f2295f04909a8e0e9
+size 43393

ppo-LunarLander-v2/system_info.txt

@@ -1,7 +1,7 @@
-OS: Linux-5.10.147+-x86_64-with-glibc2.27 #1 SMP Sat Dec 10 16:00:40 UTC 2022
-Python: 3.8.16
-Stable-Baselines3: 1.6.2
-PyTorch: 1.13.0+cu116
-GPU Enabled: True
-Numpy: 1.21.6
-Gym: 0.21.0
+- 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: 1.22.4
+- Gym: 0.21.0

results.json

@@ -1 +1 @@
-{"mean_reward": 237.40649313778204, "std_reward": 60.97994815769953, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-04T14:16:36.755735"}
+{"mean_reward": 254.2663790679206, "std_reward": 17.91029243246619, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-08T14:23:22.221262"}