Upload PPO LunarLander-v2 trained agent - gamma = 0.999

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 266.41 +/- 25.71
+      value: 231.21 +/- 64.26
       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 0x7f7c29a945e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7c29a94670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7c29a94700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7c29a94790>", "_build": "<function ActorCriticPolicy._build at 0x7f7c29a94820>", "forward": "<function ActorCriticPolicy.forward at 0x7f7c29a948b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7c29a94940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7c29a949d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7c29a94a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7c29a94af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7c29a94b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7c29a8ce10>"}, "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": 1670605951847441273, "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 0x7f7c29a945e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7c29a94670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7c29a94700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7c29a94790>", "_build": "<function ActorCriticPolicy._build at 0x7f7c29a94820>", "forward": "<function ActorCriticPolicy.forward at 0x7f7c29a948b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7c29a94940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7c29a949d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7c29a94a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7c29a94af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7c29a94b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7c29a8ce10>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670614036158491054, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_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": 124, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.95, "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:f0c363160dd1ba0d7811ce7580fafa0b2ed3f2518d253610910de9f02da3e0f9
-size 147182
+oid sha256:f435c7323dd64c7a9baefa7a35e29593955a0a8304160e77b6cfb16ef88b2115
+size 147184

ppo-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 507904,
+    "_total_timesteps": 500000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1670605951847441273,
+    "start_time": 1670614036158491054,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJqk/L2eq68/64/QvuVTs77UFWG+w+FSvgAAAAAAAAAAmgTcPdwkRz7q4iC+RLlSvqNUqjttj7+7AAAAAAAAAACz7yO9NrCJPxmlmr3O9sm+5UHTva7V0D0AAAAAAAAAAJoq4zyuCY+6OlHnN/6X0DLiK6i5U08GtwAAgD8AAIA/Te9avSnkSroLVTSzcecjL9AYGDvT/8AzAACAPwAAgD+AbJu90uC7uy4LXztmJkY9rkgavSO8IT4AAAAAAACAP7PuRT0DHgW8/Y+0O5tjlTzKZl496l15vQAAgD8AAIA/zRTTPQRXXT8PbpU9FfPQvgd3iD1rN8O9AAAAAAAAAACappk8kHq+P6kOMj4MdWQ+h6z9u4aDLj0AAAAAAAAAACaSej5Qp34/JNOLPvuSFb+7GY0+GlFIPAAAAAAAAAAAAP+vPHsam7qaXyY2WpfoMHv8jTprZkC1AACAPwAAgD/zp9U98nQoPkelPb7g/2u+ewpFvfrSVb0AAAAAAAAAAAAYwjvIkZQ9O+srvVRIkr5VL2C9fWMyvQAAAAAAAAAAZrq3PNTs+j12n1G+TLN8vvEJC70fXwM+AAAAAAAAAAANNh8+SH+JP7Xivj4sMRe/4rJuPjZ2Oz4AAAAAAAAAAACa/jxSqLa7e9gfO9ezozzvpQo9//iJvQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -69,16 +69,16 @@
     "_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'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 248,
+    "_n_updates": 124,
     "n_steps": 1024,
     "gamma": 0.999,
-    "gae_lambda": 0.98,
+    "gae_lambda": 0.95,
     "ent_coef": 0.01,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3374b351efacdcf3588372cf2527e6c241cbb68af39834e6763302928f689a10
+oid sha256:ce41a47e6994036a71364c9cdc22e674450e966dc92ef6aa439f0e690a45696c
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9ec52dcc46a2fbdfb1b09115c1eac8723c104cbf818336182298c5036150382a
+oid sha256:7049534b29c56f3d28ef350802d6d9543e00f5b89a301de38dffa667ec28e4a6
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 266.4145021280189, "std_reward": 25.70849612479145, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-09T17:59:52.192980"}
+{"mean_reward": 231.2121060140537, "std_reward": 64.2563775416391, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-09T19:36:55.413108"}