Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -92.97 +/- 43.74
+      value: 280.04 +/- 17.38
       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 0x7f228fb2fe20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f228fb2feb0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f228fb2ff40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f228fb48040>", "_build": "<function ActorCriticPolicy._build at 0x7f228fb480d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f228fb48160>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f228fb481f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f228fb48280>", "_predict": "<function ActorCriticPolicy._predict at 0x7f228fb48310>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f228fb483a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f228fb48430>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f228fb484c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f228fb443c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 0, "_total_timesteps": 10000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1698207138287156101, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 1.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 0, "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": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 10240, "n_epochs": 5, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.5.6-76060506-generic-x86_64-with-glibc2.35 # 202310061235~1697396945~22.04~9283e32 SMP PREEMPT_DYNAMIC Sun O", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.1.0", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1"}}
+{"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 0x7cb1e7eb0670>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cb1e7eb0700>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cb1e7eb0790>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cb1e7eb0820>", "_build": "<function ActorCriticPolicy._build at 0x7cb1e7eb08b0>", "forward": "<function ActorCriticPolicy.forward at 0x7cb1e7eb0940>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cb1e7eb09d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cb1e7eb0a60>", "_predict": "<function ActorCriticPolicy._predict at 0x7cb1e7eb0af0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cb1e7eb0b80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cb1e7eb0c10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cb1e7eb0ca0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cb1e7ea9480>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1698211267408405571, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_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": 248, "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": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:51fb28ff4d49043faa9f4d17d56a282b72230296d1b4767563395c2bd3c893cd
-size 148059
+oid sha256:27a28e95c07fcb87f91f6422b98fa773deffe138ea3ce4f8753748bb229cc4eb
+size 148010

ppo-LunarLander-v2/data

@@ -4,20 +4,20 @@
         ":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 0x7904f7501360>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7904f75013f0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7904f7501480>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7904f7501510>",
-        "_build": "<function ActorCriticPolicy._build at 0x7904f75015a0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7904f7501630>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7904f75016c0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7904f7501750>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7904f75017e0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7904f7501870>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7904f7501900>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7904f7501990>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7cb1e7eb0670>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cb1e7eb0700>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cb1e7eb0790>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cb1e7eb0820>",
+        "_build": "<function ActorCriticPolicy._build at 0x7cb1e7eb08b0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7cb1e7eb0940>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cb1e7eb09d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cb1e7eb0a60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7cb1e7eb0af0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cb1e7eb0b80>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cb1e7eb0c10>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cb1e7eb0ca0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7904f74fcd00>"
+        "_abc_impl": "<_abc._abc_data object at 0x7cb1e7ea9480>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -26,12 +26,12 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1698200629693153580,
+    "start_time": 1698211267408405571,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -45,7 +45,7 @@
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWVIQwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHMwfpUxVQ2MAWyUTQIBjAF0lEdAkGE+7xusLnV9lChoBkdAcrSqMWGh3GgHS/JoCEdAkGHIHHFPznV9lChoBkdAcRZDyvs7dWgHS+VoCEdAkGLxe9i+c3V9lChoBkdAcAlbeMyaeGgHTQoBaAhHQJBjQDFId2h1fZQoaAZHQHBOJ6t1ZDBoB02UAWgIR0CQY2EUj9n9dX2UKGgGR0BzPyzHCGeuaAdNHQFoCEdAkGOk6PsAvXV9lChoBkdAbuKBK+SKWWgHTQ8BaAhHQJBj3b8FY+11fZQoaAZHQHE10YKpkwxoB00QAWgIR0CQZCgbp/wzdX2UKGgGR0BuuW6Ae7tiaAdL5WgIR0CQZRoy9EkTdX2UKGgGR0BykJTl1bJPaAdL7mgIR0CQZaYekpI+dX2UKGgGR0BvjK2Dxsl+aAdNOgFoCEdAkGX5jYqXnnV9lChoBkdAb1eH446wMmgHTQ0BaAhHQJBmIxyn1nN1fZQoaAZHQG6yMySFGodoB00sAWgIR0CQZwuLrHENdX2UKGgGR0BzTUUwi7kGaAdNAwFoCEdAkGcoht+CsnV9lChoBkdAbZHeMQ2/BWgHTRkBaAhHQJBoAAOrhit1fZQoaAZHQHDg9QsPJ7toB0vZaAhHQJBoLV7Qb+91fZQoaAZHQG0q7rTpgThoB00XAWgIR0CQaDZbpu/DdX2UKGgGR0Bu2LFhoduHaAdNBwFoCEdAkGjfsu3+dnV9lChoBkdAcPvmJFb3XmgHS+loCEdAkGpkdeY2KnV9lChoBkdAcFSAlfJFLGgHTRABaAhHQJBq/ZlFtsN1fZQoaAZHQHFgslHBk7RoB00DAWgIR0CQav24/eLvdX2UKGgGR0Bu+EwtapxWaAdNNAFoCEdAkGvSAxzq8nV9lChoBkdAcH2txdY4hmgHTRUBaAhHQJBsH5dnkDJ1fZQoaAZHQHOfb7O3UhFoB00yAWgIR0CQbCXPJJXhdX2UKGgGR0BxqYphF3INaAdNDQFoCEdAkGzlIuoP1HV9lChoBkdAcU8FzdUKiWgHTQUBaAhHQJBtPriVB2R1fZQoaAZHQHCI8wDeTFFoB00DAWgIR0CQbanFo+OfdX2UKGgGR0BwoaXTmW+oaAdNCwFoCEdAkG296ol2NnV9lChoBkdAcL8B0IToMmgHS+poCEdAkG3Ot4iX6nV9lChoBkdAcGBlchTwUmgHS/5oCEdAkG9D+NtIkXV9lChoBkdAcbAaef7Jn2gHS/loCEdAkG9T3IuGsXV9lChoBkdAbmArwvxpc2gHTR8BaAhHQJBvWf8Muvl1fZQoaAZHQG28PBacI7hoB00IAWgIR0CQb6ZIg/1QdX2UKGgGR0ByTUYzi0fHaAdNHQFoCEdAkHDkDQqqfnV9lChoBkdAcYQkuHvc8GgHTQkBaAhHQJBx25/b0vp1fZQoaAZHQHEDdYfW+XZoB00EAWgIR0CQcj19v0iAdX2UKGgGR0BujVGy5Zr6aAdNDQFoCEdAkHJ9lZowmHV9lChoBkdAb8IziS7oS2gHS+poCEdAkHNdv0h/zHV9lChoBkdAcbwAG0NSZWgHTRIBaAhHQJBzfaK1og51fZQoaAZHQHJRkyYXwb5oB0vaaAhHQJBzopjMFEB1fZQoaAZHQHItKtxMnJFoB0vyaAhHQJBz5TFVDKJ1fZQoaAZHQHBUKk690zVoB0vzaAhHQJCJ0BFNL151fZQoaAZHQG4JvMr3CbdoB00QAWgIR0CQiwj7ALy+dX2UKGgGR0ByKYXVLBbfaAdL5GgIR0CQi78UmD15dX2UKGgGR0BwClzgdfb9aAdL/GgIR0CQjNXhfjS5dX2UKGgGR0BxWQHPeHi4aAdNBAFoCEdAkI0ecc2itnV9lChoBkdAcqJa72+PBGgHTQwBaAhHQJCOKCuloDh1fZQoaAZHQHDOjZ+QU6BoB0v/aAhHQJCPwbn5i3J1fZQoaAZHQHLHooRZlnRoB0vyaAhHQJCRHMRpUPx1fZQoaAZHQG6fXYUWVNZoB0v4aAhHQJCRkt7KJVN1fZQoaAZHQHG6zIvJzT5oB00QAWgIR0CQkaO+IuXedX2UKGgGR0Bw2g+kgwGoaAdL7mgIR0CQkmQv6CUYdX2UKGgGR0Bw0R9F4LThaAdL7WgIR0CQk007bL2YdX2UKGgGR0ByyYrSVnmJaAdNFQFoCEdAkJNV05lvqHV9lChoBkdAcC+WNm16V2gHTRoBaAhHQJCTo+W4Vh11fZQoaAZHQHC2XGn4wh5oB00JAWgIR0CQlP0k4WDZdX2UKGgGR0BwV65c1O0taAdNSwFoCEdAkJWWVmjCYXV9lChoBkdAc8hiTt9hJGgHTQABaAhHQJCV4gow22p1fZQoaAZHQHC74EW69TRoB00QAWgIR0CQloSyMUAUdX2UKGgGR0By/nVrhzeXaAdNLQFoCEdAkJaE74i5eHV9lChoBkdAcWoltj0+T2gHTa8CaAhHQJCX2r2g3991fZQoaAZHQHBWV2mpEQZoB00nAWgIR0CQl+YWtU4rdX2UKGgGR0BvPIC8vmHQaAdNBQFoCEdAkJf02cawU3V9lChoBkdAbaTtBOYYzmgHS+toCEdAkJixXjlxO3V9lChoBkdAcTNEmplz2mgHS+1oCEdAkJixsMy8BnV9lChoBkdAcS2abWmP52gHTR8BaAhHQJCZqbSZ0CB1fZQoaAZHQHKvSgkC3gFoB0vwaAhHQJCaWkxh2GJ1fZQoaAZHQHDwCvC/Gl1oB00TAWgIR0CQmoYLLIPtdX2UKGgGR0ByeLEVFhG6aAdNCAFoCEdAkJsESh8IA3V9lChoBkdAc44U4rBj4GgHS9hoCEdAkJsqvq1PWXV9lChoBkdAcPGzyBkI5mgHTRgBaAhHQJCbp5KODJ51fZQoaAZHQHOKemelKsdoB0vpaAhHQJCdGMIeHSF1fZQoaAZHQG70oh6jWTZoB00bAWgIR0CQnabYsd1ddX2UKGgGR0BxZd9Sde6aaAdL4WgIR0CQnlHMEA5rdX2UKGgGR0BxFagRK6FuaAdNFgFoCEdAkJ5xd2PkrHV9lChoBkdAcgkJrLyMDWgHTTUBaAhHQJCetlMAWBV1fZQoaAZHQHKY1PepGWloB0vXaAhHQJCeyJ79hql1fZQoaAZHQHOYHzQNTcZoB0v5aAhHQJCe6imEXch1fZQoaAZHQHAhTB/I8yNoB00GAWgIR0CQoBRaX8fndX2UKGgGR0Bw7aUFB6a9aAdNKQFoCEdAkKBJGWldknV9lChoBkdAcHe+UhV2imgHS+1oCEdAkKBgO8TSLXV9lChoBkdAYmG3RXwLE2gHTegDaAhHQJCgrCtRvWJ1fZQoaAZHQHA2460Y0l9oB0v5aAhHQJChUXdj5Kx1fZQoaAZHQHIXpMcp9Z1oB00GAWgIR0CQodU2kzoEdX2UKGgGR0BursyrPt2LaAdL9GgIR0CQopIDoyKvdX2UKGgGR0ByUnGGVRk3aAdNEgFoCEdAkKK2UB4lhXV9lChoBkdAb0lQ79ycTmgHS9VoCEdAkKOcJ+lTFXV9lChoBkdAc8PByS3b22gHTSwBaAhHQJCjoJQcghd1fZQoaAZHQHLwnZ5AyEdoB00IAWgIR0CQpIlnyup0dX2UKGgGR0ByKnvCuU2UaAdL8GgIR0CQpREbHZK4dX2UKGgGR0BtqHhVENONaAdL+mgIR0CQpeKP4mCzdX2UKGgGR0Bu95QaaTfSaAdNDQFoCEdAkKYxE4Nqg3V9lChoBkdAcLv2g3974WgHS9poCEdAkKa5HVf/m3V9lChoBkdAcpfZaFEiMmgHTQ4BaAhHQJCmucx0uDl1fZQoaAZHQHBRthE0BOpoB00eAWgIR0CQpwsUIsy0dX2UKGgGR0Bv7Q7o0Q9SaAdNAAFoCEdAkKezLjghr3V9lChoBkdAcfXwGW2PUGgHTRcBaAhHQJCoKlSCOFR1fZQoaAZHQHNPsk2P1ctoB00KAWgIR0CQqGKRuCPIdX2UKGgGR0BxuzfrKNhmaAdNDgFoCEdAkKkw6p5u63V9lChoBkdAcsTn5zo2XWgHTQwBaAhHQJCppZr56+p1ZS4="
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
@@ -83,7 +83,7 @@
     "ent_coef": 0.01,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,
-    "batch_size": 256,
+    "batch_size": 64,
     "n_epochs": 4,
     "clip_range": {
         ":type:": "<class 'function'>",

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d3618a2ed7ffe509300fb031cff37777434c89a2852ca00ddbeaac506f726902
+oid sha256:e7c8e60df3407f375c510470f8eb666160bd670c3caf68cc5f8de7ac3f1860d7
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6eb2e0df5b73326565f74845eedfe506c34cdd7953eec6505905cf444719e0fe
+oid sha256:1913ab1700180ca890a8d3988fba25268d29729b0ea17b18f38e94d9206ce1d4
 size 43762

results.json

@@ -1 +1 @@
-{"mean_reward": -92.9704844, "std_reward": 43.7440458674056, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-25T14:12:20.139122"}
+{"mean_reward": 280.04105, "std_reward": 17.38200150831363, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-25T05:40:42.518363"}