Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 268.79 +/- 17.08
+      value: 281.16 +/- 12.38
       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 0x7f2cc36625e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2cc3662670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2cc3662700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2cc3662790>", "_build": "<function ActorCriticPolicy._build at 0x7f2cc3662820>", "forward": "<function ActorCriticPolicy.forward at 0x7f2cc36628b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2cc3662940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2cc36629d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2cc3662a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2cc3662af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2cc3662b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2cc3657e70>"}, "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": 32, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670809658785834166, "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_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": 496, "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": 8, "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 0x7f2cc36625e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f2cc3662670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2cc3662700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f2cc3662790>", "_build": "<function ActorCriticPolicy._build at 0x7f2cc3662820>", "forward": "<function ActorCriticPolicy.forward at 0x7f2cc36628b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f2cc3662940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f2cc36629d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f2cc3662a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f2cc3662af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f2cc3662b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f2cc3657e70>"}, "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": 32, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670812289077985435, "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_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": 744, "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": 8, "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:a2affc4936b8228a32864514ea496e69b6f0b332ae05224a44ae1448ac4ce176
+oid sha256:cbd0f8cfc5727bb652769b22af5a5d1ff3660fc6c3b6919e27fbb2ee946f8adf
 size 147790

ppo-LunarLander-v2/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 32,
-    "num_timesteps": 2031616,
-    "_total_timesteps": 2000000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1670809658785834166,
+    "start_time": 1670812289077985435,
     "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'>",
@@ -69,13 +69,13 @@
     "_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": 496,
+    "_n_updates": 744,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ac853ffd365c0f94df4627b8de49e4cf392f4b9a681abb5b95189bfc71e118aa
+oid sha256:f7896f1fc07899057a37b6224cd31e877c728c04106380be5591fe9a98e69a55
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1f4a811fa59012c9207fe7a5311a59755490fc9580a80b7224339c445f1a26e9
+oid sha256:125f7c746569b13932c60082f67fb869c4774b5c017a72ccc926f9076c5acb56
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 268.7929750461547, "std_reward": 17.083380235884164, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-12T02:28:28.207732"}
+{"mean_reward": 281.1573183723861, "std_reward": 12.37651473075748, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-12T02:47:08.070052"}