Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 72.18 +/- 118.58
+      value: 273.62 +/- 14.03
       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 0x7f1c6d8077e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1c6d807880>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1c6d807920>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1c6d8079c0>", "_build": "<function ActorCriticPolicy._build at 0x7f1c6d807a60>", "forward": "<function ActorCriticPolicy.forward at 0x7f1c6d807b00>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1c6d807ba0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1c6d807c40>", "_predict": "<function ActorCriticPolicy._predict at 0x7f1c6d807ce0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1c6d807d80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1c6d807e20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1c6d807ec0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f1c6d967cc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1755099909906766057, "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": 124, "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": 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-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 0x7bf59116ca40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bf59116cae0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bf59116cb80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bf59116cc20>", "_build": "<function ActorCriticPolicy._build at 0x7bf59116ccc0>", "forward": "<function ActorCriticPolicy.forward at 0x7bf59116cd60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bf59116ce00>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bf59116cea0>", "_predict": "<function ActorCriticPolicy._predict at 0x7bf59116cf40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bf59116cfe0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bf59116d080>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bf59116d120>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bf5912f5680>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1755146137676042646, "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": -0.004885333333333408, "_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": 368, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdwIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBNudW1weS5fY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolggAAAAAAAAAAQEBAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBEolggAAAAAAAAAAQEBAQEBAQGUaBVLCIWUaBl0lFKUjAZfc2hhcGWUSwiFlIwDbG93lGgRKJYgAAAAAAAAAAAAtMIAALTCAACgwAAAoMDbD0nAAACgwAAAAIAAAACAlGgLSwiFlGgZdJRSlIwEaGlnaJRoESiWIAAAAAAAAAAAALRCAAC0QgAAoEAAAKBA2w9JQAAAoEAAAIA/AACAP5RoC0sIhZRoGXSUUpSMCGxvd19yZXBylIxbWy05MC4gICAgICAgIC05MC4gICAgICAgICAtNS4gICAgICAgICAtNS4gICAgICAgICAtMy4xNDE1OTI3ICAtNS4KICAtMC4gICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMU1s5MC4gICAgICAgIDkwLiAgICAgICAgIDUuICAgICAgICAgNS4gICAgICAgICAzLjE0MTU5MjcgIDUuCiAgMS4gICAgICAgICAxLiAgICAgICBdlIwKX25wX3JhbmRvbZROdWIu", "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": 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-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:edaf39b916f33fdf6e8f2b1848682230c1668c7936c8bbc671aaee9eae0a3323
-size 148122
+oid sha256:4a915f01664e150ef36781ae9021d29925910fad2746147a88e1f76fa4212510
+size 148084

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 0x7f1c6d8077e0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1c6d807880>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1c6d807920>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1c6d8079c0>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f1c6d807a60>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f1c6d807b00>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1c6d807ba0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1c6d807c40>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f1c6d807ce0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1c6d807d80>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1c6d807e20>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1c6d807ec0>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7bf59116ca40>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bf59116cae0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bf59116cb80>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bf59116cc20>",
+        "_build": "<function ActorCriticPolicy._build at 0x7bf59116ccc0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7bf59116cd60>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bf59116ce00>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bf59116cea0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7bf59116cf40>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bf59116cfe0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bf59116d080>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bf59116d120>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f1c6d967cc0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7bf5912f5680>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "num_timesteps": 1507328,
+    "_total_timesteps": 1500000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1755099909906766057,
+    "start_time": 1755146137676042646,
     "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": -0.015808000000000044,
+    "_current_progress_remaining": -0.004885333333333408,
     "_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": 124,
+    "_n_updates": 368,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8f827f8159a0f6f960475d98146c8df6f70f935b924d3699354d69fe58e15b41
+oid sha256:1959d66b52bc81f14b22fee5d5b3e9a07f142eb3a7f0fec12f5226e9de6d9cc7
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:dcaa4540ed9898612c8c1d50ef7e3855f5969695eb2ee4f42862da51c198cb26
+oid sha256:728ebf8c57a10485d81138514c3e171ade7c2ecbf2bae368a51a2ea55201e395
 size 43762

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:195c1076ac4925086a0c6dfd35e90fe524925e0a8e59313c53bc57133d1c624c
-size 177121
+oid sha256:dab6f3317fb34d0d8d55b0ac4bbc88e2b1acd3bfd2fb03caf8711c0e82bb4066
+size 159658

results.json

@@ -1 +1 @@
-{"mean_reward": 72.1773290435829, "std_reward": 118.58399838816939, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-08-13T16:11:06.226911"}
+{"mean_reward": 273.6209976, "std_reward": 14.034611993518116, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-08-14T05:24:13.742111"}