Upload PPO LunarLander-v2 trained agent v.2

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 147.61 +/- 122.04
+      value: 259.42 +/- 14.50
       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 0x787102dcf600>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787102dcf6a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787102dcf740>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787102dcf7e0>", "_build": "<function ActorCriticPolicy._build at 0x787102dcf880>", "forward": "<function ActorCriticPolicy.forward at 0x787102dcf920>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x787102dcf9c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787102dcfa60>", "_predict": "<function ActorCriticPolicy._predict at 0x787102dcfb00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787102dcfba0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787102dcfc40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x787102dcfce0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78710362d800>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1003520, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1749915895883164454, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "_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": 2450, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 256, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 512, "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "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 0x7ff7501e40e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff7501e4180>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff7501e4220>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff7501e42c0>", "_build": "<function ActorCriticPolicy._build at 0x7ff7501e4360>", "forward": "<function ActorCriticPolicy.forward at 0x7ff7501e4400>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff7501e44a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff7501e4540>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff7501e45e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff7501e4680>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff7501e4720>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff7501e47c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ff75015dd40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1749966517790112771, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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": 128, "n_epochs": 8, "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "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 sha256:1eac2b1a1a7fc5551610765fa26b9f50bbc4374663236a770159e7d1e04b3dbe
-size 148135
+oid sha256:39843af42761040f0801cf4f408d7c157b19279365fb4bddd1bd95ca20a6c55b
+size 148133

ppo-LunarLander-v2/data

@@ -4,34 +4,34 @@
         ":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 0x787102dcf600>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787102dcf6a0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787102dcf740>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787102dcf7e0>",
-        "_build": "<function ActorCriticPolicy._build at 0x787102dcf880>",
-        "forward": "<function ActorCriticPolicy.forward at 0x787102dcf920>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x787102dcf9c0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787102dcfa60>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x787102dcfb00>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787102dcfba0>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787102dcfc40>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x787102dcfce0>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7ff7501e40e0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff7501e4180>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff7501e4220>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff7501e42c0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ff7501e4360>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ff7501e4400>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff7501e44a0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff7501e4540>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ff7501e45e0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff7501e4680>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff7501e4720>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff7501e47c0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x78710362d800>"
+        "_abc_impl": "<_abc._abc_data object at 0x7ff75015dd40>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 1003520,
+    "num_timesteps": 1015808,
     "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1749915895883164454,
+    "start_time": 1749966517790112771,
     "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'>",
@@ -41,17 +41,17 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.0035199999999999676,
+    "_current_progress_remaining": -0.015808000000000044,
     "_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": 2450,
+    "_n_updates": 248,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",
@@ -77,14 +77,14 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "n_steps": 256,
+    "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": 512,
-    "n_epochs": 10,
+    "batch_size": 128,
+    "n_epochs": 8,
     "clip_range": {
         ":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:adeec54b7ee0dca69c7a546855008df1ed1852f776972e3556514c1156713c40
+oid sha256:0580d16b753df761caa6ea4a94c3b80bc32287178579dbafe48748f5409428a4
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0149dd46b33edcd0cdc2c26248a898dac98d5afba0485dcdf187b31436b9cf01
+oid sha256:04deaee8f114e8ab91a896f345b26aa87a2771a6b3f2e85d57b6b8460db385fb
 size 43762

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d3add54c9ef21dee0e5f9f82031721e874b123146f50e0d7581804e8121fd8a2
-size 159903
+oid sha256:7ad50af5131d39a04432dfe7f7e131aedf07fc3b4b443ada8e3b4c8f84a72d8c
+size 161510

results.json

@@ -1 +1 @@
-{"mean_reward": 147.6073949, "std_reward": 122.04174145283346, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-06-14T16:27:28.610678"}
+{"mean_reward": 259.419708, "std_reward": 14.49622649155238, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-06-15T06:08:36.767718"}