push into the hub the trained PPO on LunarLander-v2 enviroment

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -419.22 +/- 81.93
+      value: 263.83 +/- 14.63
       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 0x7f7ef391ddc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7ef391de50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7ef391dee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7ef391df70>", "_build": "<function ActorCriticPolicy._build at 0x7f7ef3922040>", "forward": "<function ActorCriticPolicy.forward at 0x7f7ef39220d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7ef3922160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7ef39221f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7ef3922280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7ef3922310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7ef39223a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7ef3922430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7ef391f270>"}, "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": 1673380357045284876, "learning_rate": 3e-05, "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:": "gAWVKBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIXvI/+bvDM0CUhpRSlIwBbJRLtIwBdJRHQHNfVhb4agp1fZQoaAZoCWgPQwgrTN9rCDo1wJSGlFKUaBVLsmgWR0BzY5yFPBSDdX2UKGgGaAloD0MIQQ3fwrpNTcCUhpRSlGgVS2ZoFkdAc2Rh3JPqLXV9lChoBmgJaA9DCF6FlJ9Ui0jAlIaUUpRoFUuEaBZHQHNklCkXUH91fZQoaAZoCWgPQwij5qvkY1cZwJSGlFKUaBVLumgWR0BzaByOq//OdX2UKGgGaAloD0MIOiAJ+3ZiT0CUhpRSlGgVTegDaBZHQHNoILsrupl1fZQoaAZoCWgPQwgi4Xt/g1lZwJSGlFKUaBVLpGgWR0BzamyOaOPvdX2UKGgGaAloD0MIoGzKFd71F8CUhpRSlGgVS25oFkdAc2slrM1TBXV9lChoBmgJaA9DCNE8gEV+vT3AlIaUUpRoFUuhaBZHQHNrck2P1ct1fZQoaAZoCWgPQwjd0mpI3ExSwJSGlFKUaBVLn2gWR0Bza6pm29csdX2UKGgGaAloD0MI5ljeVQ+Y9r+UhpRSlGgVS61oFkdAc3HuwX668XV9lChoBmgJaA9DCA1TW+og7xbAlIaUUpRoFUtlaBZHQHNza2jO9nN1fZQoaAZoCWgPQwgFoidlUicyQJSGlFKUaBVLd2gWR0BzdYXJo0yhdX2UKGgGaAloD0MI8YRefxJfIsCUhpRSlGgVS5ZoFkdAc3YHJtBOYnV9lChoBmgJaA9DCAgCZOjY90XAlIaUUpRoFUt+aBZHQHN+rEtNBWx1fZQoaAZoCWgPQwjWV1cFamEawJSGlFKUaBVLlWgWR0BzfxX4j8k2dX2UKGgGaAloD0MIzAwbZf1SQ8CUhpRSlGgVS/RoFkdAc4I6guh9LHV9lChoBmgJaA9DCBWOIJVit0LAlIaUUpRoFUuSaBZHQHODHTRYzSF1fZQoaAZoCWgPQwgwYwrWOOFDwJSGlFKUaBVLo2gWR0BzhJSXMQmNdX2UKGgGaAloD0MIpP0PsFbpRMCUhpRSlGgVS6RoFkdAc4YZ1V5rxnV9lChoBmgJaA9DCHzzGyYaEDPAlIaUUpRoFUvlaBZHQHOJg5imVJN1fZQoaAZoCWgPQwgddt8xPIYtQJSGlFKUaBVLdGgWR0BziYntv4ucdX2UKGgGaAloD0MIoIhFDDvsFcCUhpRSlGgVS4xoFkdAc44jT8YQ8XV9lChoBmgJaA9DCBCWsaGbG1nAlIaUUpRoFUupaBZHQHOQhdt2s7x1fZQoaAZoCWgPQwjSpuoe2Q5WQJSGlFKUaBVN6ANoFkdAc5Wp5eJHiHV9lChoBmgJaA9DCIuKOJ1kDzDAlIaUUpRoFUviaBZHQHOYmCqZML51fZQoaAZoCWgPQwjbUDHO34tewJSGlFKUaBVLYWgWR0BzmjKzRhMKdX2UKGgGaAloD0MI5iSUvhAqOsCUhpRSlGgVS4JoFkdAc5sPkq+ajXV9lChoBmgJaA9DCEChnj4CPUXAlIaUUpRoFUusaBZHQHOc7dnCfpV1fZQoaAZoCWgPQwh56LtbWfI1wJSGlFKUaBVLtmgWR0Bzni8scyWSdX2UKGgGaAloD0MIigYpeArFS8CUhpRSlGgVS7VoFkdAc6Hvjfek6HV9lChoBmgJaA9DCKJBCp5CzhtAlIaUUpRoFUuWaBZHQHPuaSPluFZ1fZQoaAZoCWgPQwifrBiuDkAVwJSGlFKUaBVLcmgWR0Bz7w/lhgE2dX2UKGgGaAloD0MImrFoOjsZGcCUhpRSlGgVS8loFkdAc/AMC9ytFXV9lChoBmgJaA9DCFySA3Y1KURAlIaUUpRoFUuOaBZHQHP75zT4L1F1fZQoaAZoCWgPQwjHvI44ZIPgv5SGlFKUaBVL+mgWR0Bz/CKEWZZ0dX2UKGgGaAloD0MIQzunWaBtHkCUhpRSlGgVS5RoFkdAc/9LPldTpHV9lChoBmgJaA9DCJZ4QNmUo0dAlIaUUpRoFUu2aBZHQHQANu1ndwh1fZQoaAZoCWgPQwh4mWGjrLcywJSGlFKUaBVLiGgWR0B0Abr/sE7odX2UKGgGaAloD0MI1H5rJ0qGT8CUhpRSlGgVS+hoFkdAdAHvZAY51nV9lChoBmgJaA9DCIjaNoyC2C9AlIaUUpRoFUt2aBZHQHQFUYoAn2J1fZQoaAZoCWgPQwgv3o/bLx8pQJSGlFKUaBVLi2gWR0B0CCvRqoIfdX2UKGgGaAloD0MIhLuzdtsVS8CUhpRSlGgVS8toFkdAdAymNipeeHV9lChoBmgJaA9DCMmqCDcZNRNAlIaUUpRoFU3oA2gWR0B0EYQjD8+BdX2UKGgGaAloD0MICeHRxhFTNcCUhpRSlGgVTegDaBZHQHQVtO2y9mJ1fZQoaAZoCWgPQwh8mL1sO+UjwJSGlFKUaBVL4mgWR0B0F3kKeCkHdX2UKGgGaAloD0MIpztPPGenOECUhpRSlGgVS4BoFkdAdBfFiay8jHV9lChoBmgJaA9DCFCLwcO0VzrAlIaUUpRoFUuaaBZHQHQYeumrKeV1fZQoaAZoCWgPQwisrG2Kx80yQJSGlFKUaBVLyWgWR0B0H/ZElVtGdX2UKGgGaAloD0MI81gzMsg7S8CUhpRSlGgVS7VoFkdAdCGGIsRQJ3V9lChoBmgJaA9DCP2/6siR0jtAlIaUUpRoFUumaBZHQHQiQJswco91fZQoaAZoCWgPQwi6aTNOQzQHwJSGlFKUaBVLhmgWR0B0I2fzz3AVdX2UKGgGaAloD0MIT8sPXOUzQUCUhpRSlGgVS9loFkdAdCdpjc2zfXV9lChoBmgJaA9DCJgYy/RLGkpAlIaUUpRoFU3oA2gWR0B0KJR3u/lAdX2UKGgGaAloD0MIPdS2YRTWRUCUhpRSlGgVS5xoFkdAdCrIQe3hGnV9lChoBmgJaA9DCB6jPPNyWFLAlIaUUpRoFUuOaBZHQHQsI7Rv3rV1fZQoaAZoCWgPQwh2OLpKd5coQJSGlFKUaBVL3mgWR0B0LQbLlmvodX2UKGgGaAloD0MIiIGufQG95z+UhpRSlGgVS65oFkdAdDJqjrRjSXV9lChoBmgJaA9DCF7zqs5qYS7AlIaUUpRoFUupaBZHQHQyaABkqc51fZQoaAZoCWgPQwinlq31RRo7wJSGlFKUaBVLf2gWR0B0NJxCIDYAdX2UKGgGaAloD0MIhqsDIO60TcCUhpRSlGgVS4xoFkdAdDVBClabF3V9lChoBmgJaA9DCGhCk8SS3jLAlIaUUpRoFUvGaBZHQHQ1yGetjkN1fZQoaAZoCWgPQwhwBn+/mLdMwJSGlFKUaBVLb2gWR0B0OIQcxTKldX2UKGgGaAloD0MIgJpattZnI0CUhpRSlGgVS35oFkdAdDmvovBacXV9lChoBmgJaA9DCPwaSYJwWTRAlIaUUpRoFUuWaBZHQHQ5uMMqjJx1fZQoaAZoCWgPQwjSxhFr8XU8QJSGlFKUaBVLdGgWR0B0PibgCOm0dX2UKGgGaAloD0MIRfXWwFYBJ8CUhpRSlGgVS3NoFkdAdEb+TNdJKHV9lChoBmgJaA9DCJPGaB1VwTPAlIaUUpRoFUvwaBZHQHRHWKhtcfN1fZQoaAZoCWgPQwgUz9kCQr1XwJSGlFKUaBVLnmgWR0B0TAfEGZ/kdX2UKGgGaAloD0MIEAcJUb4aS8CUhpRSlGgVS7VoFkdAdFA0Rvm5lXV9lChoBmgJaA9DCF9cqtIWmFzAlIaUUpRoFU35AWgWR0B0U4yqMm4RdX2UKGgGaAloD0MIHy+kw0OYD8CUhpRSlGgVS7hoFkdAdFR8B+4LC3V9lChoBmgJaA9DCOsfRDLk2B/AlIaUUpRoFU0DAWgWR0B0VtDPWxyGdX2UKGgGaAloD0MIX0VGB6TAasCUhpRSlGgVS7doFkdAdFhn4wh4dXV9lChoBmgJaA9DCD51rFJ6li1AlIaUUpRoFUu1aBZHQHRZekxh2GJ1fZQoaAZoCWgPQwi8lLpkHD5QQJSGlFKUaBVN6ANoFkdAdFt1klNUO3V9lChoBmgJaA9DCNF2TN2VNTBAlIaUUpRoFUvraBZHQHReVuzhP0t1fZQoaAZoCWgPQwg9RQ4RN+M9QJSGlFKUaBVLsmgWR0B0XklfJFLGdX2UKGgGaAloD0MIDLCPTl21UMCUhpRSlGgVS9loFkdAdF+eizsyBXV9lChoBmgJaA9DCC/9S1KZsEXAlIaUUpRoFUucaBZHQHRnKNQ0oBt1fZQoaAZoCWgPQwg3UOCdfHomQJSGlFKUaBVLlmgWR0B0aeIMz/IbdX2UKGgGaAloD0MIdZSD2QTUVMCUhpRSlGgVS3JoFkdAdGv2fTTfBXV9lChoBmgJaA9DCIGVQ4tsLzdAlIaUUpRoFUuLaBZHQHRtteUpuuR1fZQoaAZoCWgPQwj2Yign2qk9QJSGlFKUaBVL42gWR0B0bqXeFcptdX2UKGgGaAloD0MIpIl3gCfpNsCUhpRSlGgVS6JoFkdAdHOMewLVnXV9lChoBmgJaA9DCFqEYitopjhAlIaUUpRoFUuMaBZHQHR1sQiA2AJ1fZQoaAZoCWgPQwg6QDBHj+tHwJSGlFKUaBVL4WgWR0B0epVhkRSQdX2UKGgGaAloD0MIDat4I/NcM8CUhpRSlGgVS/JoFkdAdH7kWykbgnV9lChoBmgJaA9DCPW52or9KTNAlIaUUpRoFUuOaBZHQHSEiWZ7Xxx1fZQoaAZoCWgPQwiR8SiV8DQywJSGlFKUaBVL0mgWR0B0hSakRBeHdX2UKGgGaAloD0MI+62dKAkFMkCUhpRSlGgVS2loFkdAdIgw97ngYXV9lChoBmgJaA9DCBtjJ7wEKU3AlIaUUpRoFUuRaBZHQHSJ4l2NedF1fZQoaAZoCWgPQwj7zi9K0IVQwJSGlFKUaBVLnmgWR0B0in2Xb/OudX2UKGgGaAloD0MIea7vw0HKJcCUhpRSlGgVTQUBaBZHQHSN2DQJHAh1fZQoaAZoCWgPQwhKDW0ANvZKwJSGlFKUaBVLt2gWR0B0ksK2KEWZdX2UKGgGaAloD0MIeeV620yDQkCUhpRSlGgVTegDaBZHQHSUnpGFzuF1fZQoaAZoCWgPQwjQYFPnUeErwJSGlFKUaBVLk2gWR0B0m63PRiPRdX2UKGgGaAloD0MIGw5LAz/0S0CUhpRSlGgVTegDaBZHQHSb10cOskp1fZQoaAZoCWgPQwgIWoEhq+dLwJSGlFKUaBVLx2gWR0B0nErEtNBXdX2UKGgGaAloD0MI/oFy274HMMCUhpRSlGgVS65oFkdAdJyA0bcXWXVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.7.0", "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 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 0x7f61a54ad940>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f61a54ad9d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f61a54ada60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f61a54adaf0>", "_build": "<function ActorCriticPolicy._build at 0x7f61a54adb80>", "forward": "<function ActorCriticPolicy.forward at 0x7f61a54adc10>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f61a54adca0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f61a54add30>", "_predict": "<function ActorCriticPolicy._predict at 0x7f61a54addc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f61a54ade50>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f61a54adee0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f61a54adf70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f61a54a3ea0>"}, "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": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1674411122020650635, "learning_rate": {":type:": "<class 'function'>", ":serialized:": "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"}, "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": -0.004885333333333408, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 736, "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-5.10.147+-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": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3915ffc3515c9a827bccded7333ebfafd9dc12c3cd3358fed5ed7da35aabde1b
-size 147305
+oid sha256:5c65ac728bb2443cf72a5d1bb4dc09ec6eb4815e1d9b41335b0e353ee954aee7
+size 148760

ppo-LunarLander-v2/data

@@ -4,20 +4,20 @@
         ":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 0x7f7ef391ddc0>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7ef391de50>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7ef391dee0>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7ef391df70>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f7ef3922040>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f7ef39220d0>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7ef3922160>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7ef39221f0>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f7ef3922280>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7ef3922310>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7ef39223a0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7ef3922430>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f61a54ad940>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f61a54ad9d0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f61a54ada60>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f61a54adaf0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f61a54adb80>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f61a54adc10>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f61a54adca0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f61a54add30>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f61a54addc0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f61a54ade50>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f61a54adee0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f61a54adf70>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc_data object at 0x7f7ef391f270>"
+        "_abc_impl": "<_abc_data object at 0x7f61a54a3ea0>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -43,21 +43,24 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "num_timesteps": 3014656,
+    "_total_timesteps": 3000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1673380357045284876,
-    "learning_rate": 3e-05,
+    "start_time": 1674411122020650635,
+    "learning_rate": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
     "tensorboard_log": null,
     "lr_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -67,16 +70,16 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.004885333333333408,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "gAWVKBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIXvI/+bvDM0CUhpRSlIwBbJRLtIwBdJRHQHNfVhb4agp1fZQoaAZoCWgPQwgrTN9rCDo1wJSGlFKUaBVLsmgWR0BzY5yFPBSDdX2UKGgGaAloD0MIQQ3fwrpNTcCUhpRSlGgVS2ZoFkdAc2Rh3JPqLXV9lChoBmgJaA9DCF6FlJ9Ui0jAlIaUUpRoFUuEaBZHQHNklCkXUH91fZQoaAZoCWgPQwij5qvkY1cZwJSGlFKUaBVLumgWR0BzaByOq//OdX2UKGgGaAloD0MIOiAJ+3ZiT0CUhpRSlGgVTegDaBZHQHNoILsrupl1fZQoaAZoCWgPQwgi4Xt/g1lZwJSGlFKUaBVLpGgWR0BzamyOaOPvdX2UKGgGaAloD0MIoGzKFd71F8CUhpRSlGgVS25oFkdAc2slrM1TBXV9lChoBmgJaA9DCNE8gEV+vT3AlIaUUpRoFUuhaBZHQHNrck2P1ct1fZQoaAZoCWgPQwjd0mpI3ExSwJSGlFKUaBVLn2gWR0Bza6pm29csdX2UKGgGaAloD0MI5ljeVQ+Y9r+UhpRSlGgVS61oFkdAc3HuwX668XV9lChoBmgJaA9DCA1TW+og7xbAlIaUUpRoFUtlaBZHQHNza2jO9nN1fZQoaAZoCWgPQwgFoidlUicyQJSGlFKUaBVLd2gWR0BzdYXJo0yhdX2UKGgGaAloD0MI8YRefxJfIsCUhpRSlGgVS5ZoFkdAc3YHJtBOYnV9lChoBmgJaA9DCAgCZOjY90XAlIaUUpRoFUt+aBZHQHN+rEtNBWx1fZQoaAZoCWgPQwjWV1cFamEawJSGlFKUaBVLlWgWR0BzfxX4j8k2dX2UKGgGaAloD0MIzAwbZf1SQ8CUhpRSlGgVS/RoFkdAc4I6guh9LHV9lChoBmgJaA9DCBWOIJVit0LAlIaUUpRoFUuSaBZHQHODHTRYzSF1fZQoaAZoCWgPQwgwYwrWOOFDwJSGlFKUaBVLo2gWR0BzhJSXMQmNdX2UKGgGaAloD0MIpP0PsFbpRMCUhpRSlGgVS6RoFkdAc4YZ1V5rxnV9lChoBmgJaA9DCHzzGyYaEDPAlIaUUpRoFUvlaBZHQHOJg5imVJN1fZQoaAZoCWgPQwgddt8xPIYtQJSGlFKUaBVLdGgWR0BziYntv4ucdX2UKGgGaAloD0MIoIhFDDvsFcCUhpRSlGgVS4xoFkdAc44jT8YQ8XV9lChoBmgJaA9DCBCWsaGbG1nAlIaUUpRoFUupaBZHQHOQhdt2s7x1fZQoaAZoCWgPQwjSpuoe2Q5WQJSGlFKUaBVN6ANoFkdAc5Wp5eJHiHV9lChoBmgJaA9DCIuKOJ1kDzDAlIaUUpRoFUviaBZHQHOYmCqZML51fZQoaAZoCWgPQwjbUDHO34tewJSGlFKUaBVLYWgWR0BzmjKzRhMKdX2UKGgGaAloD0MI5iSUvhAqOsCUhpRSlGgVS4JoFkdAc5sPkq+ajXV9lChoBmgJaA9DCEChnj4CPUXAlIaUUpRoFUusaBZHQHOc7dnCfpV1fZQoaAZoCWgPQwh56LtbWfI1wJSGlFKUaBVLtmgWR0Bzni8scyWSdX2UKGgGaAloD0MIigYpeArFS8CUhpRSlGgVS7VoFkdAc6Hvjfek6HV9lChoBmgJaA9DCKJBCp5CzhtAlIaUUpRoFUuWaBZHQHPuaSPluFZ1fZQoaAZoCWgPQwifrBiuDkAVwJSGlFKUaBVLcmgWR0Bz7w/lhgE2dX2UKGgGaAloD0MImrFoOjsZGcCUhpRSlGgVS8loFkdAc/AMC9ytFXV9lChoBmgJaA9DCFySA3Y1KURAlIaUUpRoFUuOaBZHQHP75zT4L1F1fZQoaAZoCWgPQwjHvI44ZIPgv5SGlFKUaBVL+mgWR0Bz/CKEWZZ0dX2UKGgGaAloD0MIQzunWaBtHkCUhpRSlGgVS5RoFkdAc/9LPldTpHV9lChoBmgJaA9DCJZ4QNmUo0dAlIaUUpRoFUu2aBZHQHQANu1ndwh1fZQoaAZoCWgPQwh4mWGjrLcywJSGlFKUaBVLiGgWR0B0Abr/sE7odX2UKGgGaAloD0MI1H5rJ0qGT8CUhpRSlGgVS+hoFkdAdAHvZAY51nV9lChoBmgJaA9DCIjaNoyC2C9AlIaUUpRoFUt2aBZHQHQFUYoAn2J1fZQoaAZoCWgPQwgv3o/bLx8pQJSGlFKUaBVLi2gWR0B0CCvRqoIfdX2UKGgGaAloD0MIhLuzdtsVS8CUhpRSlGgVS8toFkdAdAymNipeeHV9lChoBmgJaA9DCMmqCDcZNRNAlIaUUpRoFU3oA2gWR0B0EYQjD8+BdX2UKGgGaAloD0MICeHRxhFTNcCUhpRSlGgVTegDaBZHQHQVtO2y9mJ1fZQoaAZoCWgPQwh8mL1sO+UjwJSGlFKUaBVL4mgWR0B0F3kKeCkHdX2UKGgGaAloD0MIpztPPGenOECUhpRSlGgVS4BoFkdAdBfFiay8jHV9lChoBmgJaA9DCFCLwcO0VzrAlIaUUpRoFUuaaBZHQHQYeumrKeV1fZQoaAZoCWgPQwisrG2Kx80yQJSGlFKUaBVLyWgWR0B0H/ZElVtGdX2UKGgGaAloD0MI81gzMsg7S8CUhpRSlGgVS7VoFkdAdCGGIsRQJ3V9lChoBmgJaA9DCP2/6siR0jtAlIaUUpRoFUumaBZHQHQiQJswco91fZQoaAZoCWgPQwi6aTNOQzQHwJSGlFKUaBVLhmgWR0B0I2fzz3AVdX2UKGgGaAloD0MIT8sPXOUzQUCUhpRSlGgVS9loFkdAdCdpjc2zfXV9lChoBmgJaA9DCJgYy/RLGkpAlIaUUpRoFU3oA2gWR0B0KJR3u/lAdX2UKGgGaAloD0MIPdS2YRTWRUCUhpRSlGgVS5xoFkdAdCrIQe3hGnV9lChoBmgJaA9DCB6jPPNyWFLAlIaUUpRoFUuOaBZHQHQsI7Rv3rV1fZQoaAZoCWgPQwh2OLpKd5coQJSGlFKUaBVL3mgWR0B0LQbLlmvodX2UKGgGaAloD0MIiIGufQG95z+UhpRSlGgVS65oFkdAdDJqjrRjSXV9lChoBmgJaA9DCF7zqs5qYS7AlIaUUpRoFUupaBZHQHQyaABkqc51fZQoaAZoCWgPQwinlq31RRo7wJSGlFKUaBVLf2gWR0B0NJxCIDYAdX2UKGgGaAloD0MIhqsDIO60TcCUhpRSlGgVS4xoFkdAdDVBClabF3V9lChoBmgJaA9DCGhCk8SS3jLAlIaUUpRoFUvGaBZHQHQ1yGetjkN1fZQoaAZoCWgPQwhwBn+/mLdMwJSGlFKUaBVLb2gWR0B0OIQcxTKldX2UKGgGaAloD0MIgJpattZnI0CUhpRSlGgVS35oFkdAdDmvovBacXV9lChoBmgJaA9DCPwaSYJwWTRAlIaUUpRoFUuWaBZHQHQ5uMMqjJx1fZQoaAZoCWgPQwjSxhFr8XU8QJSGlFKUaBVLdGgWR0B0PibgCOm0dX2UKGgGaAloD0MIRfXWwFYBJ8CUhpRSlGgVS3NoFkdAdEb+TNdJKHV9lChoBmgJaA9DCJPGaB1VwTPAlIaUUpRoFUvwaBZHQHRHWKhtcfN1fZQoaAZoCWgPQwgUz9kCQr1XwJSGlFKUaBVLnmgWR0B0TAfEGZ/kdX2UKGgGaAloD0MIEAcJUb4aS8CUhpRSlGgVS7VoFkdAdFA0Rvm5lXV9lChoBmgJaA9DCF9cqtIWmFzAlIaUUpRoFU35AWgWR0B0U4yqMm4RdX2UKGgGaAloD0MIHy+kw0OYD8CUhpRSlGgVS7hoFkdAdFR8B+4LC3V9lChoBmgJaA9DCOsfRDLk2B/AlIaUUpRoFU0DAWgWR0B0VtDPWxyGdX2UKGgGaAloD0MIX0VGB6TAasCUhpRSlGgVS7doFkdAdFhn4wh4dXV9lChoBmgJaA9DCD51rFJ6li1AlIaUUpRoFUu1aBZHQHRZekxh2GJ1fZQoaAZoCWgPQwi8lLpkHD5QQJSGlFKUaBVN6ANoFkdAdFt1klNUO3V9lChoBmgJaA9DCNF2TN2VNTBAlIaUUpRoFUvraBZHQHReVuzhP0t1fZQoaAZoCWgPQwg9RQ4RN+M9QJSGlFKUaBVLsmgWR0B0XklfJFLGdX2UKGgGaAloD0MIDLCPTl21UMCUhpRSlGgVS9loFkdAdF+eizsyBXV9lChoBmgJaA9DCC/9S1KZsEXAlIaUUpRoFUucaBZHQHRnKNQ0oBt1fZQoaAZoCWgPQwg3UOCdfHomQJSGlFKUaBVLlmgWR0B0aeIMz/IbdX2UKGgGaAloD0MIdZSD2QTUVMCUhpRSlGgVS3JoFkdAdGv2fTTfBXV9lChoBmgJaA9DCIGVQ4tsLzdAlIaUUpRoFUuLaBZHQHRtteUpuuR1fZQoaAZoCWgPQwj2Yign2qk9QJSGlFKUaBVL42gWR0B0bqXeFcptdX2UKGgGaAloD0MIpIl3gCfpNsCUhpRSlGgVS6JoFkdAdHOMewLVnXV9lChoBmgJaA9DCFqEYitopjhAlIaUUpRoFUuMaBZHQHR1sQiA2AJ1fZQoaAZoCWgPQwg6QDBHj+tHwJSGlFKUaBVL4WgWR0B0epVhkRSQdX2UKGgGaAloD0MIDat4I/NcM8CUhpRSlGgVS/JoFkdAdH7kWykbgnV9lChoBmgJaA9DCPW52or9KTNAlIaUUpRoFUuOaBZHQHSEiWZ7Xxx1fZQoaAZoCWgPQwiR8SiV8DQywJSGlFKUaBVL0mgWR0B0hSakRBeHdX2UKGgGaAloD0MI+62dKAkFMkCUhpRSlGgVS2loFkdAdIgw97ngYXV9lChoBmgJaA9DCBtjJ7wEKU3AlIaUUpRoFUuRaBZHQHSJ4l2NedF1fZQoaAZoCWgPQwj7zi9K0IVQwJSGlFKUaBVLnmgWR0B0in2Xb/OudX2UKGgGaAloD0MIea7vw0HKJcCUhpRSlGgVTQUBaBZHQHSN2DQJHAh1fZQoaAZoCWgPQwhKDW0ANvZKwJSGlFKUaBVLt2gWR0B0ksK2KEWZdX2UKGgGaAloD0MIeeV620yDQkCUhpRSlGgVTegDaBZHQHSUnpGFzuF1fZQoaAZoCWgPQwjQYFPnUeErwJSGlFKUaBVLk2gWR0B0m63PRiPRdX2UKGgGaAloD0MIGw5LAz/0S0CUhpRSlGgVTegDaBZHQHSb10cOskp1fZQoaAZoCWgPQwgIWoEhq+dLwJSGlFKUaBVLx2gWR0B0nErEtNBXdX2UKGgGaAloD0MI/oFy274HMMCUhpRSlGgVS65oFkdAdJyA0bcXWXVlLg=="
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 124,
+    "_n_updates": 736,
     "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 sha256:19b94eceb2a92081734a1f5574a93a7994961ca4d7c940de5f0607d14cd9cb63
+oid sha256:0e30e195d9667ed73ce0185fbb6552a3baecab1826e417d235bb37a4867bc041
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:84c3ab83a2a413b6eaaee89682cd8951e283ecb57dfa854ed120410155b0db2a
+oid sha256:690b70478d930b1bb8cd5ce88c3d3620eb23b3bd6e80d2ebc13ea40e4cc9967b
 size 43393

ppo-LunarLander-v2/system_info.txt

@@ -1,7 +1,7 @@
-- OS: Linux-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
-- Python: 3.8.16
+- 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: 1.13.0+cu116
+- PyTorch: 1.13.1+cu116
 - GPU Enabled: True
 - Numpy: 1.21.6
 - Gym: 0.21.0

results.json

@@ -1 +1 @@
-{"mean_reward": -419.21919420065825, "std_reward": 81.93454661596289, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-10T20:00:25.793677"}
+{"mean_reward": 263.83084134431425, "std_reward": 14.629681111230889, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-22T19:06:44.385013"}