retrained

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -496.22 +/- 221.60
+      value: -130.58 +/- 24.19
       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 0x7c9df07d7250>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c9df07d72e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c9df07d7370>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c9df07d7400>", "_build": "<function ActorCriticPolicy._build at 0x7c9df07d7490>", "forward": "<function ActorCriticPolicy.forward at 0x7c9df07d7520>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c9df07d75b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c9df07d7640>", "_predict": "<function ActorCriticPolicy._predict at 0x7c9df07d76d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c9df07d7760>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c9df07d77f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c9df07d7880>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c9df10fa340>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 131072, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1717465907532326961, "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": -0.3107200000000001, "_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": 40, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
+{"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 0x797db4c05800>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x797db4c058a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x797db4c05940>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x797db4c059e0>", "_build": "<function ActorCriticPolicy._build at 0x797db4c05a80>", "forward": "<function ActorCriticPolicy.forward at 0x797db4c05b20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x797db4c05bc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x797db4c05c60>", "_predict": "<function ActorCriticPolicy._predict at 0x797db4c05d00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x797db4c05da0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x797db4c05e40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x797db4c05ee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x797db4d68800>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 229376, "_total_timesteps": 200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1740008756157405530, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAABAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.1468799999999999, "_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": 70, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "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 sha256:3b7f17d249d57480b7a7fe5a229c8d0c148f7d2dcc7874b38acedf0ddda96c20
-size 147946
+oid sha256:14df5a397a035afa67fb6786804b38cb9489338601226151b922fe387f7e84ef
+size 148026

ppo-LunarLander-v2/data

@@ -4,54 +4,54 @@
         ":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 0x7c9df07d7250>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c9df07d72e0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c9df07d7370>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c9df07d7400>",
-        "_build": "<function ActorCriticPolicy._build at 0x7c9df07d7490>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7c9df07d7520>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c9df07d75b0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c9df07d7640>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7c9df07d76d0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c9df07d7760>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c9df07d77f0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c9df07d7880>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x797db4c05800>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x797db4c058a0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x797db4c05940>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x797db4c059e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x797db4c05a80>",
+        "forward": "<function ActorCriticPolicy.forward at 0x797db4c05b20>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x797db4c05bc0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x797db4c05c60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x797db4c05d00>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x797db4c05da0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x797db4c05e40>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x797db4c05ee0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7c9df10fa340>"
+        "_abc_impl": "<_abc._abc_data object at 0x797db4d68800>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 131072,
-    "_total_timesteps": 100000,
+    "num_timesteps": 229376,
+    "_total_timesteps": 200000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1717465907532326961,
+    "start_time": 1740008756157405530,
     "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'>",
-        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAABAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
     },
     "_last_original_obs": null,
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.3107200000000001,
+    "_current_progress_remaining": -0.1468799999999999,
     "_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": 40,
+    "_n_updates": 70,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",
@@ -87,13 +87,13 @@
     "n_epochs": 10,
     "clip_range": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":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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"
+        ":serialized:": "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"
     }
 }

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3738b682bb036b6b4c08c048839080dff387ddecbc687d2ac5737b0fd5e5cfcf
+oid sha256:d35fef5d09293ce4f1c6c3e0c3410c1ade34f3f79e32e273ad1c541890e98126
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5b632b5ad17b7984d84ef07d435d6e9be7f9535585ecab9a072f388f9d88f009
+oid sha256:a769944e7544c8d70b58adfa1e95ab35ca4b6f18f4f8cfb38776aecd73e84500
 size 43762

ppo-LunarLander-v2/system_info.txt

@@ -1,9 +1,9 @@
-- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
-- Python: 3.10.12
+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.11.11
 - Stable-Baselines3: 2.0.0a5
-- PyTorch: 2.3.0+cu121
+- PyTorch: 2.5.1+cu124
 - GPU Enabled: True
-- Numpy: 1.25.2
-- Cloudpickle: 2.2.1
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.1
 - Gymnasium: 0.28.1
 - OpenAI Gym: 0.25.2

results.json

@@ -1 +1 @@
-{"mean_reward": -496.21622400000007, "std_reward": 221.60155993951088, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-04T01:59:59.614437"}
+{"mean_reward": -130.57739709999998, "std_reward": 24.186496721808354, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-02-20T00:16:11.900079"}