PPO model for lunar lander

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 259.14 +/- 20.47
+      value: 273.60 +/- 26.82
       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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f6b3f81cca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6b3f81cd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6b3f81cdc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6b3f81ce50>", "_build": "<function ActorCriticPolicy._build at 0x7f6b3f81cee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f6b3f81cf70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6b3f821040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6b3f8210d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6b3f821160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6b3f8211f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6b3f821280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f6b3f8994b0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1672313154055488617, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "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, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
+{"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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f30a7c7bca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f30a7c7bd30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f30a7c7bdc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f30a7c7be50>", "_build": "<function ActorCriticPolicy._build at 0x7f30a7c7bee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f30a7c7bf70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f30a7c01040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f30a7c010d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f30a7c01160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f30a7c011f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f30a7c01280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f30a7c793f0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1672323326593682078, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "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, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ba695c07aefe73820795ca0a4068e196366154e3d5aa744010f5a0608f073f18
-size 147210
+oid sha256:1491aa53382e70001e951bb441c4998b104a72b9f2702474b74875eed9e1edf8
+size 147174

ppo-LunarLander-v2/data

@@ -4,19 +4,19 @@
         ":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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f6b3f81cca0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6b3f81cd30>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6b3f81cdc0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6b3f81ce50>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f6b3f81cee0>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f6b3f81cf70>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6b3f821040>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f6b3f8210d0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6b3f821160>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6b3f8211f0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6b3f821280>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f30a7c7bca0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f30a7c7bd30>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f30a7c7bdc0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f30a7c7be50>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f30a7c7bee0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f30a7c7bf70>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f30a7c01040>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f30a7c010d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f30a7c01160>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f30a7c011f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f30a7c01280>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f6b3f8994b0>"
+        "_abc_impl": "<_abc_data object at 0x7f30a7c793f0>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -47,7 +47,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1672313154055488617,
+    "start_time": 1672323326593682078,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -69,7 +69,7 @@
     "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d94fd591c1e9bdf09e65405c385e1dd0ce66d09d77a43f440c10d5fd0026fba6
+oid sha256:72ed3ee9c92c8c8c53e55b8eca9051d62ef6bebc71b7ec36a1539c53d9a4fc7f
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:33fa58d1c21bb3bd7d7c492e61f3ce6a0a21bd53523c67021a09110ea1512931
+oid sha256:bc61f1a44aed5880ce3e3b14e82652a0a33976ab24763083ed084601cbb623e0
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 259.13946032809474, "std_reward": 20.466828252374558, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-29T11:44:05.505930"}
+{"mean_reward": 273.5952346063592, "std_reward": 26.816452307944925, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-29T14:34:22.878071"}