first trained model using PPO method to LunarLander-v2 env

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -476.13 +/- 254.46
+      value: 281.52 +/- 16.91
       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 0x7f63a1755d30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f63a1755dc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f63a1755e50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f63a1755ee0>", "_build": "<function ActorCriticPolicy._build at 0x7f63a1755f70>", "forward": "<function ActorCriticPolicy.forward at 0x7f63a1759040>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f63a17590d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f63a1759160>", "_predict": "<function ActorCriticPolicy._predict at 0x7f63a17591f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f63a1759280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f63a1759310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f63a17593a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f63a17526f0>"}, "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": 16384, "_total_timesteps": 1000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677525566085490468, "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": -15.384, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4, "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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "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 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 0x7f63a1755d30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f63a1755dc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f63a1755e50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f63a1755ee0>", "_build": "<function ActorCriticPolicy._build at 0x7f63a1755f70>", "forward": "<function ActorCriticPolicy.forward at 0x7f63a1759040>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f63a17590d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f63a1759160>", "_predict": "<function ActorCriticPolicy._predict at 0x7f63a17591f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f63a1759280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f63a1759310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f63a17593a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f63a17526f0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 5013504, "_total_timesteps": 5000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677525915317350309, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+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": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI5Nh6hjAsckCUhpRSlIwBbJRLt4wBdJRHQLnoMQ1aW5Z1fZQoaAZoCWgPQwhJ1XYTvMdxQJSGlFKUaBVLoGgWR0C56DjQJHAidX2UKGgGaAloD0MIiUM2kG7BcECUhpRSlGgVS4FoFkdAueg/CfpUxXV9lChoBmgJaA9DCCYd5WB2u3JAlIaUUpRoFUubaBZHQLnoQN4Z/Ct1fZQoaAZoCWgPQwitFAK5xPtyQJSGlFKUaBVLuGgWR0C56EJmZmZmdX2UKGgGaAloD0MIT6+UZUjoc0CUhpRSlGgVS9NoFkdAuehNF6RhdHV9lChoBmgJaA9DCETgSKDBxHJAlIaUUpRoFUvCaBZHQLnoWB5X2dx1fZQoaAZoCWgPQwj1EI3uIJZwQJSGlFKUaBVLlmgWR0C56F+GbkOqdX2UKGgGaAloD0MIFNBE2HD5c0CUhpRSlGgVS7toFkdAuehhiobXH3V9lChoBmgJaA9DCIoGKXjKA3FAlIaUUpRoFUuGaBZHQLnoZXI2fkF1fZQoaAZoCWgPQwgmNEks6apxQJSGlFKUaBVLfWgWR0C56HSsOoYOdX2UKGgGaAloD0MIhiFy+noiOECUhpRSlGgVS2RoFkdAueiErTYukHV9lChoBmgJaA9DCHFyv0NR73JAlIaUUpRoFUvSaBZHQLnoiNfPX051fZQoaAZoCWgPQwis4o3MYxBzQJSGlFKUaBVLrmgWR0C56I3TiKixdX2UKGgGaAloD0MIhel7DcFzcECUhpRSlGgVS45oFkdAueiYzoEB83V9lChoBmgJaA9DCGKelbTiD3NAlIaUUpRoFUuNaBZHQLnorE6T4cp1fZQoaAZoCWgPQwjzOXe73nVwQJSGlFKUaBVLiWgWR0C56M4iLVFydX2UKGgGaAloD0MIVDVB1P3kckCUhpRSlGgVS5FoFkdAuejQ9FF2FHV9lChoBmgJaA9DCExRLo2fKHNAlIaUUpRoFUujaBZHQLno3p4rz5J1fZQoaAZoCWgPQwikMzDyssJwQJSGlFKUaBVLnGgWR0C56OUZvUBodX2UKGgGaAloD0MIthSQ9j/8cUCUhpRSlGgVS51oFkdAuejniIcin3V9lChoBmgJaA9DCN1hE5n5AXJAlIaUUpRoFUuAaBZHQLno6URnOB11fZQoaAZoCWgPQwitp1ZfHSxyQJSGlFKUaBVLoGgWR0C56PTpPhybdX2UKGgGaAloD0MIl8YvvFJWckCUhpRSlGgVS51oFkdAuekD5wfhdnV9lChoBmgJaA9DCNpU3SMbbHBAlIaUUpRoFUuZaBZHQLnpBczZYgd1fZQoaAZoCWgPQwgJTn0guXhxQJSGlFKUaBVLiWgWR0C56RNXHR1HdX2UKGgGaAloD0MIE5m5wKWYcUCUhpRSlGgVS7doFkdAuekWj9GZu3V9lChoBmgJaA9DCH6s4LfhX3FAlIaUUpRoFUumaBZHQLnpIRjBl+V1fZQoaAZoCWgPQwjFkQcii91vQJSGlFKUaBVLn2gWR0C56S11SwW4dX2UKGgGaAloD0MIbF1qhL5wc0CUhpRSlGgVS6FoFkdAuek0bHZK4HV9lChoBmgJaA9DCFtfJLQlU3NAlIaUUpRoFUubaBZHQLnpUCuU2UB1fZQoaAZoCWgPQwjSNv5EJXVxQJSGlFKUaBVLrWgWR0C56U8gyM1kdX2UKGgGaAloD0MIgLVq10R4cUCUhpRSlGgVS39oFkdAuelV/axoqXV9lChoBmgJaA9DCLDo1mt6Mk1AlIaUUpRoFUt3aBZHQLnpYj2SMcZ1fZQoaAZoCWgPQwhznNuEO6JxQJSGlFKUaBVLiWgWR0C56W/l6qsEdX2UKGgGaAloD0MIxY1bzI8hcUCUhpRSlGgVS51oFkdAuel1/G2kSHV9lChoBmgJaA9DCICaWrZWnXJAlIaUUpRoFUuyaBZHQLnpqapgkTp1fZQoaAZoCWgPQwh5knTNJFBzQJSGlFKUaBVLtmgWR0C56ayNfgJkdX2UKGgGaAloD0MIf2ySH/E+b0CUhpRSlGgVS51oFkdAuemxTzd1uHV9lChoBmgJaA9DCIFc4shDpHFAlIaUUpRoFUu2aBZHQLnpvFjurp91fZQoaAZoCWgPQwiYwRiRKK9xQJSGlFKUaBVLpGgWR0C56cvigkC4dX2UKGgGaAloD0MISn7Er5jIcECUhpRSlGgVS6VoFkdAuenQP8Q7LnV9lChoBmgJaA9DCHU90XWhQ3JAlIaUUpRoFUuPaBZHQLnp2K4QSSN1fZQoaAZoCWgPQwh4uYjvRL9zQJSGlFKUaBVLzmgWR0C56erPyCnQdX2UKGgGaAloD0MIhSf0+hNFckCUhpRSlGgVS4poFkdAuentOARTTHV9lChoBmgJaA9DCOs1PSgo7nNAlIaUUpRoFUu5aBZHQLnp/xFAmiR1fZQoaAZoCWgPQwhGYKxvILVyQJSGlFKUaBVLyWgWR0C56gNHH3lCdX2UKGgGaAloD0MI0GBT55EUckCUhpRSlGgVS6JoFkdAueoNTAFgUnV9lChoBmgJaA9DCNZuu9BcCnNAlIaUUpRoFUunaBZHQLnqDT850bN1fZQoaAZoCWgPQwiH4LiMGwlyQJSGlFKUaBVLoWgWR0C56hXWrfcfdX2UKGgGaAloD0MIjbPpCKBccUCUhpRSlGgVS5ZoFkdAueocOmR/3HV9lChoBmgJaA9DCO1GH/NB8HBAlIaUUpRoFUu9aBZHQLnqPyhBZ6l1fZQoaAZoCWgPQwj8xteemT5wQJSGlFKUaBVLkmgWR0C56koLsruqdX2UKGgGaAloD0MIp1oLs1ChcECUhpRSlGgVS4loFkdAuepOtknTiXV9lChoBmgJaA9DCD0oKEXr1nBAlIaUUpRoFUudaBZHQLnqUxt52Qp1fZQoaAZoCWgPQwgBNbVsraBTQJSGlFKUaBVLUmgWR0C56mHoHLRsdX2UKGgGaAloD0MIteGwNLBVckCUhpRSlGgVS4VoFkdAuepkOTaCc3V9lChoBmgJaA9DCPw4miNrEnJAlIaUUpRoFUu2aBZHQLnqczgdfb91fZQoaAZoCWgPQwjjVGthVl9wQJSGlFKUaBVLpGgWR0C56nx46fapdX2UKGgGaAloD0MIjXqIRjcAcECUhpRSlGgVS5JoFkdAueqFGd7OV3V9lChoBmgJaA9DCPp6vmZ5E3NAlIaUUpRoFUu/aBZHQLnqlyWzF/B1fZQoaAZoCWgPQwgfoWZIVUtyQJSGlFKUaBVLj2gWR0C56ppWmxdIdX2UKGgGaAloD0MICHO7lztbcUCUhpRSlGgVS6loFkdAueqfxFy7w3V9lChoBmgJaA9DCN6Rsdq8gHFAlIaUUpRoFUufaBZHQLnqwq8UVSJ1fZQoaAZoCWgPQwhUU5J1+CVwQJSGlFKUaBVLkmgWR0C56sZm29csdX2UKGgGaAloD0MI6DOg3kxccECUhpRSlGgVS5loFkdAuerHpB5X2nV9lChoBmgJaA9DCFLTLqbZz3JAlIaUUpRoFUu7aBZHQLnq2IN3GGV1fZQoaAZoCWgPQwjueJPfIoRxQJSGlFKUaBVLhWgWR0C56vUFwDNhdX2UKGgGaAloD0MIO8JpwUvzcUCUhpRSlGgVS59oFkdAuesOioKlYXV9lChoBmgJaA9DCMO2RZnNUnBAlIaUUpRoFUuWaBZHQLnrIDbah6B1fZQoaAZoCWgPQwheS8gHfQJyQJSGlFKUaBVLhmgWR0C56zew1R+CdX2UKGgGaAloD0MIU8xB0FGBckCUhpRSlGgVS6loFkdAues4hUzbe3V9lChoBmgJaA9DCC6rsBlgq3FAlIaUUpRoFUukaBZHQLnrULE1l5J1fZQoaAZoCWgPQwgq/u+ISpJzQJSGlFKUaBVLvWgWR0C563S0OVgQdX2UKGgGaAloD0MIIH9pUR9bckCUhpRSlGgVS5BoFkdAuet9kiD/VHV9lChoBmgJaA9DCJYlOsvsrHJAlIaUUpRoFUuWaBZHQLnrisOG0u11fZQoaAZoCWgPQwgGLSRgNF5zQJSGlFKUaBVLv2gWR0C566PD+BH1dX2UKGgGaAloD0MIPZ0rSskpcUCUhpRSlGgVS5BoFkdAueusLApKBnV9lChoBmgJaA9DCPd2S3LAIXNAlIaUUpRoFUuoaBZHQLnrsAxSHdp1fZQoaAZoCWgPQwiz0w/qIglyQJSGlFKUaBVLwWgWR0C567ZWRzRydX2UKGgGaAloD0MIjQjGwSXDckCUhpRSlGgVS5hoFkdAueu8NoakynV9lChoBmgJaA9DCACt+fGXGHNAlIaUUpRoFUuoaBZHQLnr02rGR3h1fZQoaAZoCWgPQwgExvoG5lRxQJSGlFKUaBVLqmgWR0C56+dAC4jKdX2UKGgGaAloD0MIiA0WThLIckCUhpRSlGgVS6ZoFkdAuev8gvDgqHV9lChoBmgJaA9DCDrrU46J4nFAlIaUUpRoFUt/aBZHQLnr/tTkyUN1fZQoaAZoCWgPQwhlq8spgdpwQJSGlFKUaBVLjWgWR0C57BOY+jdpdX2UKGgGaAloD0MI85GU9HBfdECUhpRSlGgVS6toFkdAuewbluFYdXV9lChoBmgJaA9DCI3ROqqaqnNAlIaUUpRoFUu4aBZHQLnsPTot+Th1fZQoaAZoCWgPQwjG3/YECadyQJSGlFKUaBVLfWgWR0C57EcDwH7hdX2UKGgGaAloD0MI+PvFbAnPckCUhpRSlGgVS6RoFkdAuexN17pmmXV9lChoBmgJaA9DCNvcmJ7w/nBAlIaUUpRoFUucaBZHQLnsZJE6T4d1fZQoaAZoCWgPQwhsskY9hENxQJSGlFKUaBVLgmgWR0C57Gfa11GLdX2UKGgGaAloD0MIIQGjy5vHcECUhpRSlGgVS6FoFkdAuexzz/ZM+XV9lChoBmgJaA9DCNTVHYstX3JAlIaUUpRoFUuJaBZHQLnsebEP1+R1fZQoaAZoCWgPQwhTexFtx8xvQJSGlFKUaBVLkGgWR0C57I3bM5fddX2UKGgGaAloD0MIsTVbeQlucUCUhpRSlGgVS6RoFkdAueylbdJrcnV9lChoBmgJaA9DCF0VqMWgqXNAlIaUUpRoFUueaBZHQLnsqRT0g8t1fZQoaAZoCWgPQwh0KENVzGVwQJSGlFKUaBVLmGgWR0C57Liih37ldX2UKGgGaAloD0MICjGXVO1ocECUhpRSlGgVS4FoFkdAuezBgjQiRnV9lChoBmgJaA9DCHyYvWx7NHBAlIaUUpRoFUuLaBZHQLnszhTwUg11ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1530, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4f7f79976fe13a14ce9889ab83071c6df5a229c70033d0440160ab20a8cddbfe
-size 147271
+oid sha256:ad616f18a511641fd2961e53093c5ae9e40a847f122d340c3ae080673cd7d39c
+size 147296

ppo-LunarLander-v2/data

@@ -43,12 +43,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 16384,
-    "_total_timesteps": 1000,
+    "num_timesteps": 5013504,
+    "_total_timesteps": 5000000.0,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1677525566085490468,
+    "start_time": 1677525915317350309,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -57,7 +57,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -67,24 +67,24 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -15.384,
+    "_current_progress_remaining": -0.0027007999999999477,
     "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": 4,
-    "n_steps": 1024,
-    "gamma": 0.999,
+    "_n_updates": 1530,
+    "n_steps": 2048,
+    "gamma": 0.99,
     "gae_lambda": 0.98,
     "ent_coef": 0.01,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,
     "batch_size": 64,
-    "n_epochs": 4,
+    "n_epochs": 10,
     "clip_range": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:70089d7eb2314de8d71640a79365e47b491f2448a59f184825e7e0a1eb559d5d
+oid sha256:93e77cc5d0d3bbecd2db9c13cd0010f6c3696737da95a35c32a3a42721e38a9f
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:21f0827dd8fdfda2d3999e74260b94ca349f98119d6d72605b8511d5e38a65ff
+oid sha256:c939ef8bacc8254883eb6ece140b7691d92765116b50e659d35236e764af0dd8
 size 43393

results.json

@@ -1 +1 @@
-{"mean_reward": -476.1265967800515, "std_reward": 254.45870498803416, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-27T19:20:54.636266"}
+{"mean_reward": 281.5176592940188, "std_reward": 16.907409538064478, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-27T21:13:26.015824"}