Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -133.96 +/- 85.65
+      value: 250.81 +/- 17.22
       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 0x7d6023c2ede0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d6023c2ee80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d6023c2ef20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d6023c2efc0>", "_build": "<function ActorCriticPolicy._build at 0x7d6023c2f060>", "forward": "<function ActorCriticPolicy.forward at 0x7d6023c2f100>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d6023c2f1a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d6023c2f240>", "_predict": "<function ActorCriticPolicy._predict at 0x7d6023c2f2e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d6023c2f380>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d6023c2f420>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d6023c2f4c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d6023d80980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 212992, "_total_timesteps": 200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1745947193123614863, "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": -0.0649599999999999, "_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": 80, "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": "3.11.12", "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 0x7d9bcf947920>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d9bcf9479c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d9bcf947a60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d9bcf947b00>", "_build": "<function ActorCriticPolicy._build at 0x7d9bcf947ba0>", "forward": "<function ActorCriticPolicy.forward at 0x7d9bcf947c40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d9bcf947ce0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d9bcf947d80>", "_predict": "<function ActorCriticPolicy._predict at 0x7d9bcf947e20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d9bcf947ec0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d9bcf947f60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d9bcf94c040>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d9bcfdc5940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1746006669112775291, "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": 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": "3.11.12", "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:b2937cd82729f73326ee1dd3bdc23838afddab0dc1db91a669935e02012aa809
-size 148059
+oid sha256:e1620f44f70c8f9e9ab60b6ebd334075376f41265bca35e451332f0595e9f89b
+size 148132

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 0x7d6023c2ede0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d6023c2ee80>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d6023c2ef20>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d6023c2efc0>",
-        "_build": "<function ActorCriticPolicy._build at 0x7d6023c2f060>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7d6023c2f100>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d6023c2f1a0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d6023c2f240>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7d6023c2f2e0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d6023c2f380>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d6023c2f420>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d6023c2f4c0>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7d9bcf947920>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d9bcf9479c0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d9bcf947a60>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d9bcf947b00>",
+        "_build": "<function ActorCriticPolicy._build at 0x7d9bcf947ba0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7d9bcf947c40>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d9bcf947ce0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d9bcf947d80>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7d9bcf947e20>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d9bcf947ec0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d9bcf947f60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d9bcf94c040>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7d6023d80980>"
+        "_abc_impl": "<_abc._abc_data object at 0x7d9bcfdc5940>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 212992,
-    "_total_timesteps": 200000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1745947193123614863,
+    "start_time": 1746006669112775291,
     "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": -0.0649599999999999,
+    "_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": 80,
+    "_n_updates": 248,
     "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:ab129b1a2d69d56c493f7f2169b74348950de1f59a89fcdcefadf149c7ce1e50
+oid sha256:a4edcd09a0bcaaae82a3c52392af82c877fbf0a1c2d4ce8a6e9ec7b214238762
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:07bcd33d54d1930211fe75448629cb1908b1fb5a1aa79c37c9f3a5e09516c7ef
+oid sha256:105674bce6655105aaadf6f3477b8598e0eb7313645ba25bd1632c3db41da535
 size 43762

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f8a8ac12ff2bb170626164272b1766fb8c987723601f2ee8806308bd142b1289
-size 180211
+oid sha256:12eab393f12ef2674f4b9beb0e4371ab7a2b72c5c35cf8963c035d340e9dc8bb
+size 169512

results.json

@@ -1 +1 @@
-{"mean_reward": -133.9602811, "std_reward": 85.6510132582574, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-04-29T17:39:24.711395"}
+{"mean_reward": 250.81047327131986, "std_reward": 17.21883358859928, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-04-30T10:16:26.386935"}