Fixed Video

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 244.64 +/- 27.54
+      value: 242.08 +/- 19.81
       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 0x0000029F577FF100>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x0000029F577FF1A0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x0000029F577FF240>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x0000029F577FF2E0>", "_build": "<function ActorCriticPolicy._build at 0x0000029F577FF380>", "forward": "<function ActorCriticPolicy.forward at 0x0000029F577FF420>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x0000029F577FF4C0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x0000029F577FF560>", "_predict": "<function ActorCriticPolicy._predict at 0x0000029F577FF600>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x0000029F577FF6A0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x0000029F577FF740>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x0000029F577FF7E0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x0000029F4BE3EB00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718066712724211800, "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, "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, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Windows-10-10.0.22631-SP0 10.0.22631", "Python": "3.11.9", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0", "GPU Enabled": "True", "Numpy": "1.24.3", "Cloudpickle": "2.2.1", "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 0x00000152AD3C3100>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x00000152AD3C31A0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x00000152AD3C3240>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x00000152AD3C32E0>", "_build": "<function ActorCriticPolicy._build at 0x00000152AD3C3380>", "forward": "<function ActorCriticPolicy.forward at 0x00000152AD3C3420>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x00000152AD3C34C0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x00000152AD3C3560>", "_predict": "<function ActorCriticPolicy._predict at 0x00000152AD3C3600>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x00000152AD3C36A0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x00000152AD3C3740>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x00000152AD3C37E0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x00000152ACD74700>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718125310192881800, "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:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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": "Windows-10-10.0.22631-SP0 10.0.22631", "Python": "3.11.9", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0", "GPU Enabled": "True", "Numpy": "1.24.3", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bcfc5432782ac5dba0c0539d7ac1bf590b9dc0348232fb3e292c7159312a38f3
-size 148112
+oid sha256:59b8ce613c756f0f992674580445e2eff5ad0ddb69cc4a3c0de8b1b13c457c5a
+size 147924

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 0x0000029F577FF100>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x0000029F577FF1A0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x0000029F577FF240>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x0000029F577FF2E0>",
-        "_build": "<function ActorCriticPolicy._build at 0x0000029F577FF380>",
-        "forward": "<function ActorCriticPolicy.forward at 0x0000029F577FF420>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x0000029F577FF4C0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x0000029F577FF560>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x0000029F577FF600>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x0000029F577FF6A0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x0000029F577FF740>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x0000029F577FF7E0>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x00000152AD3C3100>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x00000152AD3C31A0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x00000152AD3C3240>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x00000152AD3C32E0>",
+        "_build": "<function ActorCriticPolicy._build at 0x00000152AD3C3380>",
+        "forward": "<function ActorCriticPolicy.forward at 0x00000152AD3C3420>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x00000152AD3C34C0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x00000152AD3C3560>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x00000152AD3C3600>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x00000152AD3C36A0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x00000152AD3C3740>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x00000152AD3C37E0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x0000029F4BE3EB00>"
+        "_abc_impl": "<_abc._abc_data object at 0x00000152ACD74700>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -26,12 +26,12 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1718066712724211800,
+    "start_time": 1718125310192881800,
     "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'>",
@@ -45,31 +45,16 @@
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "gAWVPwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQG0cEXtShraMAWyUTTMBjAF0lEdAjgzCCrcTJ3V9lChoBkdAcTQoMa0hNmgHTR0BaAhHQI43r/Khcqx1fZQoaAZHQGznys0YTCdoB01nAWgIR0CON9PPcBU8dX2UKGgGR0BxIpkf9xZMaAdNcAFoCEdAjjgwco6S1XV9lChoBkdAcJh39aUzK2gHTT8BaAhHQI44fVmSQo11fZQoaAZHQHB/W+j/MntoB01gAWgIR0COOpQKKHfudX2UKGgGR0BPwNdqtYCAaAdNGgFoCEdAjjyUdq+JxnV9lChoBkdAcQ/paA4GU2gHTRABaAhHQI486qMm4RV1fZQoaAZHQG6AvBacI7hoB01EAWgIR0COPPPOY6XCdX2UKGgGR0ButYYHgP3BaAdNUwFoCEdAjj1osAeaKHV9lChoBkdAcQox5s0pE2gHTUIBaAhHQI4+fJV81Gd1fZQoaAZHQG8EJztCzC1oB00yAWgIR0COQkJeE7GOdX2UKGgGR0BwuKxyGSIQaAdNDgFoCEdAjkPpaiblR3V9lChoBkdAcb/U2DQJHGgHTTwBaAhHQI5E1EPUayd1fZQoaAZHQHASCrPt2LZoB00VAWgIR0CORX2AXl8xdX2UKGgGR0BwHWp3os7NaAdNHgFoCEdAjkaXCj1wpHV9lChoBkdAb+SvC/GlymgHTYUBaAhHQI5Hm6ErXlN1fZQoaAZHQG7Vdat9x6xoB00yAWgIR0COR+BIWgvldX2UKGgGR0BvQxtNzr/saAdNSwFoCEdAjkib9If8uXV9lChoBkdAcazCPIXCTGgHTTYBaAhHQI5I6NfgJkZ1fZQoaAZHQE1igxJul41oB00RAWgIR0COSX2IwdsBdX2UKGgGR0ByjP7XQMQVaAdNSgFoCEdAjkmbQLNOd3V9lChoBkdANJsnJDE3sGgHS+loCEdAjknkS26TXHV9lChoBkdAb4uwh4dIXmgHTTQBaAhHQI5NuM2m52B1fZQoaAZHQHEaH+qBErpoB01xAWgIR0COUcqmTC+DdX2UKGgGR0Bvl1XiiqQzaAdNPQFoCEdAjlR256MR6HV9lChoBkdAa75bILgGbGgHTTcBaAhHQI5Xyi22G7B1fZQoaAZHQHITHb212JVoB03cAWgIR0COWCg2ZRbbdX2UKGgGR0BwSkmJFb3XaAdNSgFoCEdAjlhgmiQDFXV9lChoBkdAcgYhkRSP2mgHTV0BaAhHQI5YqIi1Rch1fZQoaAZHQD43dKujh1loB00CAWgIR0COWRi1AqusdX2UKGgGR0BwzJ2wFC9iaAdNTwFoCEdAjlq0GFBY3nV9lChoBkdAcVPxZdOZcGgHTUIBaAhHQI5bCTQmeDp1fZQoaAZHQHFO3+yZ8a5oB00/AWgIR0COW/D4QBgedX2UKGgGR0BqelbiZOSGaAdNOwFoCEdAjlwNrTH80nV9lChoBkdAa7WpfhMrVmgHTTABaAhHQI5cbyFwkxB1fZQoaAZHQHHM14keIVNoB001AWgIR0COXGjnmq5tdX2UKGgGR0Bw92gsbvPUaAdNVgFoCEdAjlx2O6unuXV9lChoBkdAbgOiILw4KmgHTSABaAhHQI5l9b1RLsd1fZQoaAZHQG/0Fo+Ofd1oB01OAWgIR0COZmJng5zYdX2UKGgGR0BrjE6FM7EHaAdNHwFoCEdAjmk/Z/Tb4HV9lChoBkdAb8E3EQ5FPWgHTc0BaAhHQI5qmNJe3QV1fZQoaAZHQHFfWeQMhHNoB00HAWgIR0COaw9HMEA6dX2UKGgGR0BtobposZpBaAdNMQFoCEdAjmsyEUTL4nV9lChoBkdAcjME1EVnEmgHTSwBaAhHQI5rlZLZi/h1fZQoaAZHQG2luzhP0qZoB001AWgIR0COa7p8neBQdX2UKGgGR0BFZS/CZWq+aAdNEAFoCEdAjm0liBoVVXV9lChoBkdAbopqesgdO2gHTSABaAhHQI5tjAi3XqZ1fZQoaAZHQHDafsZ5zHVoB000AWgIR0CObY4PwuuidX2UKGgGR0BvifLDAJswaAdNYwFoCEdAjm4E+gUUPHV9lChoBkdAcsTg/C66KGgHTTIBaAhHQI5ukM3IdU91fZQoaAZHQHHy5CF9KEpoB01HAWgIR0COb+qABkqddX2UKGgGR0BuPk9ZA6dUaAdNbAFoCEdAjnHExZdOZnV9lChoBkdAQ6Etf5ULlWgHS+hoCEdAjqAuBUaQ3nV9lChoBkdAXYTmHP/rB2gHTegDaAhHQI6jIYzi0fJ1fZQoaAZHQG/VxBeHBUJoB01HAWgIR0COozLns9jgdX2UKGgGR0BvkpfOUt7KaAdNEAFoCEdAjqQDhtLteHV9lChoBkdAcDYde6ZpjGgHTVUBaAhHQI6kWp4rz5J1fZQoaAZHQHBXs8TzundoB00xAWgIR0COpaoYvWYndX2UKGgGR0BxiO7e2uxKaAdNKAFoCEdAjqX8F6iTMnV9lChoBkdAcgy7ihnJ1mgHTVQBaAhHQI6oYE4ecQR1fZQoaAZHQHC9Uw35vcdoB01PAWgIR0COqI925hBrdX2UKGgGR0Bu26OinHeaaAdNKwFoCEdAjqi9n9NvfnV9lChoBkdAcWd974SHumgHTUIBaAhHQI6pI31jAi51fZQoaAZHQHHi6DPGACpoB008AWgIR0COqjvCuU2UdX2UKGgGR0BvdMRg7YChaAdNWQFoCEdAjqq4iosI3XV9lChoBkdAcEHPacqe9WgHTWcBaAhHQI6rXaBZpzt1fZQoaAZHQHAuADvE0i1oB002AWgIR0COrRWcSXdCdX2UKGgGR0BwmVuGbkOqaAdNagFoCEdAjq26oddVvXV9lChoBkdARdlNHpbD/GgHS+JoCEdAjrB1XV9WqHV9lChoBkdAcEcM+eOGTWgHTUEBaAhHQI6x3yd4FA51fZQoaAZHQHB3fBJqZc9oB00rAWgIR0COtJIMBp6AdX2UKGgGR0BsWaOHWSU1aAdNSwFoCEdAjrXBwVCXyHV9lChoBkdAb386iCaqj2gHTSsBaAhHQI62tOEdvKl1fZQoaAZHQG/f6Df3vhJoB00hAWgIR0COuOQe3hGZdX2UKGgGR0ByPnW6K+BZaAdNLAFoCEdAjrlqbBoEjnV9lChoBkdAcUxE/jbSJGgHTTwBaAhHQI67I33pOet1fZQoaAZHQG695hBqsU9oB00mAWgIR0COu6WcjJMhdX2UKGgGR0Bx8z28IzFdaAdNnQFoCEdAjr2065oXbnV9lChoBkdAcjFQ/oq0+mgHTVsBaAhHQI6+XxlQMx51fZQoaAZHQG8PPrGBFuxoB02WAWgIR0COv+GB4D9wdX2UKGgGR0Bxx90knkT6aAdNZgFoCEdAjsBmJm/WUnV9lChoBkdAcDw3irDIimgHTUIBaAhHQI7AcWhysCF1fZQoaAZHQHKBDfek56toB00UAWgIR0COwY7voePrdX2UKGgGR0Bx+34nF5v+aAdNIQFoCEdAjsOhhYvFnHV9lChoBkdAcEyNIsiB5GgHTXcBaAhHQI7D+bmU4aR1fZQoaAZHQHGoN6cAimloB00+AWgIR0COx3YT0xubdX2UKGgGR0Bw6MdyT6i1aAdNMgFoCEdAjsigTZg5R3V9lChoBkdAbY8WZ7Xxv2gHTUIBaAhHQI7IvgrH2h91fZQoaAZHQEJ+y+HrQgNoB0viaAhHQI7KXP9kz411fZQoaAZHQHHjrm2b5M1oB01BAWgIR0COy5t52QnydX2UKGgGR0Bujlmz0HyFaAdNKAFoCEdAjswuJUHY6HV9lChoBkdAcVyfzz3AVWgHTUgBaAhHQI7MgcWCVbB1fZQoaAZHQG7Y/ChvitJoB00cAWgIR0CO0LMQmNR4dX2UKGgGR0BxAyL4vexfaAdNGQFoCEdAjtHsEJSiunV9lChoBkdAcBt9XLeQ+2gHTUEBaAhHQI7SbkIX0oV1fZQoaAZHQG4GDM3ZPEdoB009AWgIR0CO0r9LpRoAdX2UKGgGR0BqUMW9DhLoaAdNmAFoCEdAjtOJYcNpd3V9lChoBkdAcQDpEx7AtWgHTQ4BaAhHQI7TnObAk9l1fZQoaAZHQEKbOkcjqwBoB0vVaAhHQI7UVglWwNd1ZS4="
+        ":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,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
-        ":serialized:": "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",
+        ":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]",
@@ -84,7 +69,7 @@
     },
     "action_space": {
         ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
-        ":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
         "n": "4",
         "start": "0",
         "_shape": [],
@@ -92,6 +77,21 @@
         "_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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"

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bf1959342b9c57d1c56ce531b5e70b9595c47c3a3eef83461c22883991e2b8c8
-size 88490
+oid sha256:862f966b5280c85e1ed8009ee5d3a085ad82ee7cba5df47ce0cfea9a2c145a11
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:dde1b130c4f2dcda125df7faa46203009d291dca248efd5ae7d10e48bfeec7ea
+oid sha256:996aa1612496c07d39aaa9111d38820a02bf96f800ac43c6a8386820bbf4756e
 size 43762

results.json

@@ -1 +1 @@
-{"mean_reward": 244.6360047, "std_reward": 27.54498836470092, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-11T10:06:46.133998"}
+{"mean_reward": 242.0802764, "std_reward": 19.805275794511402, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-11T11:19:06.963932"}