Upload PPO LunarLander-v2 trained agent

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: -192.92 +/- 58.23
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **LunarLander-v2**
+This is a trained model of a **PPO** agent playing **LunarLander-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

@@ -0,0 +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 0x7f8ca0e2f700>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8ca0e2f790>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8ca0e2f820>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8ca0e2f8b0>", "_build": "<function ActorCriticPolicy._build at 0x7f8ca0e2f940>", "forward": "<function ActorCriticPolicy.forward at 0x7f8ca0e2f9d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8ca0e2fa60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8ca0e2faf0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8ca0e2fb80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8ca0e2fc10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8ca0e2fca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8ca0e2fd30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f8ca0e2a7b0>"}, "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": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1677244227734958693, "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:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAOZvzD1Nuak/eB9tPnXA3r74MYI8ICYiPgAAAAAAAAAAmltEPnfahz8eV7k+K4sMvxWBMD4by2o+AAAAAAAAAAANh8o9h+p/Pl8vir1A32e/3IRIPoemuD0AAAAAAAAAALOZK72Cndc++2gevjPhNb9O6QE+grlGPQAAAAAAAAAAZrmGPeSUYz9mgh4+y1Ysv7vf+z2NnPg9AAAAAAAAAAC7r66+8eJJP3aQ6L7mPzK/FA4fvoLLzb0AAAAAAAAAAObyYD2FH7c/okZGP/BIVD0eITS9Sy5gvQAAAAAAAAAAjU5bvj/FmD8CjY2+wiSwvhLjub5Pob++AAAAAAAAAACaTlQ9oiPsPn3a4b6zLWi/GgywPnS0Gb4AAAAAAAAAAKYEhz0qzSU/zqvvPQ4jMb94gYo9BQonPgAAAAAAAAAAABnMPFTlsT/yDP4+EFZjvqUqq7ynQxe9AAAAAAAAAADNspc8hmmTP9DLXDqTivC+tlDPPQEnQj4AAAAAAAAAADuSi75WJLk/sh0ov/tycL44eBG+fTCKvgAAAAAAAAAAjZfVPWUPqz+zhpo9imfPvvbMbD4PpgI+AAAAAAAAAABmxAS86IKuP932Lb49Tb++bL4bPMteBj0AAAAAAAAAAGq7i75kRa0//MgQv63H1b5w3kW+BEcHvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": -0.1468799999999999, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIm1q21pfXYcCUhpRSlIwBbJRLiIwBdJRHQFfLhZha1Tl1fZQoaAZoCWgPQwj8UdSZe/ddwJSGlFKUaBVLf2gWR0BXzkPtlZoxdX2UKGgGaAloD0MIsMqFyr/uIsCUhpRSlGgVS05oFkdAV83m+0w8GXV9lChoBmgJaA9DCP+xEB0CylzAlIaUUpRoFUtqaBZHQFfRGH58BuJ1fZQoaAZoCWgPQwiUT49tGWhIwJSGlFKUaBVLVmgWR0BX0hNVR1oydX2UKGgGaAloD0MItFVJZB+wPECUhpRSlGgVS21oFkdAV9MMLF4s3HV9lChoBmgJaA9DCN82UyEeCTnAlIaUUpRoFUuHaBZHQFfXxASnLq51fZQoaAZoCWgPQwiFsBpLWOc/wJSGlFKUaBVLkWgWR0BX2AOJ+DvmdX2UKGgGaAloD0MIlBPtKqQeR8CUhpRSlGgVS1NoFkdAV9gpUgjhUHV9lChoBmgJaA9DCOdUMgBUZUfAlIaUUpRoFUtZaBZHQFfad3B55Z91fZQoaAZoCWgPQwioiqn0E842wJSGlFKUaBVLWGgWR0BX4NHhCMP0dX2UKGgGaAloD0MIzse1oWKUM8CUhpRSlGgVS3ZoFkdAV+E3cYZVGXV9lChoBmgJaA9DCErRyr3AY1bAlIaUUpRoFUtqaBZHQFfhNdZ7ojh1fZQoaAZoCWgPQwhYWdsUjwtAQJSGlFKUaBVLcmgWR0BX4rCrLhaUdX2UKGgGaAloD0MIXMr5Yu+fT8CUhpRSlGgVS25oFkdAV+JnRLK3eHV9lChoBmgJaA9DCKqB5nPuvifAlIaUUpRoFUt/aBZHQFfmlnyup0h1fZQoaAZoCWgPQwh0QuigS3JewJSGlFKUaBVLg2gWR0BX5v/JeVs2dX2UKGgGaAloD0MIIm3jT1RwSMCUhpRSlGgVS1toFkdAV+inxaxHG3V9lChoBmgJaA9DCBsN4C2QOD/AlIaUUpRoFUtzaBZHQFfqJFb3XZp1fZQoaAZoCWgPQwhj1SDM7UduwJSGlFKUaBVLfmgWR0BX7VDF6zE8dX2UKGgGaAloD0MIzTrj++IOMMCUhpRSlGgVS1loFkdAV+4Nx2jfvXV9lChoBmgJaA9DCKg2OBH9/krAlIaUUpRoFUt6aBZHQFfvUWl/H5t1fZQoaAZoCWgPQwj76T9rfvQ9wJSGlFKUaBVLfGgWR0BX8dXxOLzgdX2UKGgGaAloD0MIYVPnUfEKUMCUhpRSlGgVS2poFkdAV/LPw/gR9XV9lChoBmgJaA9DCE1oklhSQFDAlIaUUpRoFUtUaBZHQFf2Tvy9VWF1fZQoaAZoCWgPQwgjFFtB085OwJSGlFKUaBVLbGgWR0BX/SR8twrEdX2UKGgGaAloD0MIVFbT9US7RsCUhpRSlGgVS2xoFkdAV/0hvBJqZnV9lChoBmgJaA9DCBaiQ+BIlkrAlIaUUpRoFUuGaBZHQFf82ZiNKiB1fZQoaAZoCWgPQwjrAIi7epNOwJSGlFKUaBVLlmgWR0BX/lndweeWdX2UKGgGaAloD0MIGhnkLsIoU8CUhpRSlGgVS2RoFkdAWALim2sq8XV9lChoBmgJaA9DCNb8+EuLahfAlIaUUpRoFUtOaBZHQFgEJemelKt1fZQoaAZoCWgPQwhrfZHQllJbwJSGlFKUaBVLamgWR0BYBggX/HYIdX2UKGgGaAloD0MI0ZSdflD3MMCUhpRSlGgVS45oFkdAWAfIDHOryXV9lChoBmgJaA9DCNF3t7JEOzPAlIaUUpRoFUuRaBZHQFgIRxcVxjt1fZQoaAZoCWgPQwiQFmcMczZFwJSGlFKUaBVLhGgWR0BYCZJPIn0DdX2UKGgGaAloD0MIBD3UtmF+ScCUhpRSlGgVS4doFkdAWAoGOdXkpHV9lChoBmgJaA9DCOBm8WJhKB7AlIaUUpRoFUtgaBZHQFgL5mRNh3J1fZQoaAZoCWgPQwjEeqNWmChQwJSGlFKUaBVLdGgWR0BYDHH/95yEdX2UKGgGaAloD0MILQsm/igQQcCUhpRSlGgVS4toFkdAWBErK/20zHV9lChoBmgJaA9DCDmZuFUQ90vAlIaUUpRoFUuCaBZHQFgTb+tKZlZ1fZQoaAZoCWgPQwgWTtL8MVVIwJSGlFKUaBVLXWgWR0BYFLPdEb5udX2UKGgGaAloD0MINCxGXWvvFcCUhpRSlGgVS2NoFkdAWBYsAeaKDXV9lChoBmgJaA9DCLXhsDTw0UPAlIaUUpRoFUuLaBZHQFgZ6E8JUo91fZQoaAZoCWgPQwi9qUiFsXNIwJSGlFKUaBVLYmgWR0BYHOs5n13/dX2UKGgGaAloD0MIAOFDiZb4VMCUhpRSlGgVS2poFkdAWB3frKNhmXV9lChoBmgJaA9DCHl5OleUNFLAlIaUUpRoFUtYaBZHQFgeksz2vjh1fZQoaAZoCWgPQwhVoBaDh4kOwJSGlFKUaBVLV2gWR0BYICCWeHzpdX2UKGgGaAloD0MIyGDFqdZaN8CUhpRSlGgVS1ZoFkdAWCIQyylennV9lChoBmgJaA9DCBISaRt/8VLAlIaUUpRoFUtXaBZHQFgi1schkiF1fZQoaAZoCWgPQwjku5S6ZPhMwJSGlFKUaBVLkWgWR0BYIlHavicYdX2UKGgGaAloD0MIInGPpQ+VRMCUhpRSlGgVS3FoFkdAWCReu3c583V9lChoBmgJaA9DCBSVDWsqdlTAlIaUUpRoFUudaBZHQFgmTkyULUl1fZQoaAZoCWgPQwjzkCkfglJSwJSGlFKUaBVLgmgWR0BYJqveP7vYdX2UKGgGaAloD0MItoKmJVaqTMCUhpRSlGgVS39oFkdAWCkaOxSpBHV9lChoBmgJaA9DCKyPh767uT/AlIaUUpRoFUtQaBZHQFgo/MGHHm11fZQoaAZoCWgPQwitFthjIqhSwJSGlFKUaBVLW2gWR0BYKk9yLhrFdX2UKGgGaAloD0MI8wAW+fVzFsCUhpRSlGgVS11oFkdAWC0ZIg/1QXV9lChoBmgJaA9DCIv6JHfYtCbAlIaUUpRoFUtPaBZHQFgyWbwz+FV1fZQoaAZoCWgPQwiaJJaUu7RUwJSGlFKUaBVLZWgWR0BYNoLLIPsidX2UKGgGaAloD0MIgJ9x4UD+R8CUhpRSlGgVS55oFkdAWDjoSteUp3V9lChoBmgJaA9DCKFMo8nF7EDAlIaUUpRoFUt1aBZHQFg7YpDu0C11fZQoaAZoCWgPQwj1oKAUrVzkv5SGlFKUaBVLaWgWR0BYPIBJZntfdX2UKGgGaAloD0MIF4BG6dJjT8CUhpRSlGgVS1xoFkdAWD02WIGhVXV9lChoBmgJaA9DCPs9sU6VPUfAlIaUUpRoFUtXaBZHQFg+6QeV9nd1fZQoaAZoCWgPQwhcOuY8Y6tKwJSGlFKUaBVLiWgWR0BYP0QwsXizdX2UKGgGaAloD0MIAWiULv2PNcCUhpRSlGgVS5doFkdAWEAvIwM6R3V9lChoBmgJaA9DCEt1AS8zP1LAlIaUUpRoFUt5aBZHQFg/9ic5Ke11fZQoaAZoCWgPQwgVjbW/swxRwJSGlFKUaBVLaWgWR0BYQ3s9jgAIdX2UKGgGaAloD0MIueAM/n6lT8CUhpRSlGgVS4ZoFkdAWENBQemvXHV9lChoBmgJaA9DCNvEyf0OvUPAlIaUUpRoFUt6aBZHQFhE+8oQWep1fZQoaAZoCWgPQwjLoUW282U5wJSGlFKUaBVLZmgWR0BYRv91loUSdX2UKGgGaAloD0MI8Irgfys7R8CUhpRSlGgVS5JoFkdAWEgQtjCpFXV9lChoBmgJaA9DCBu8r8qFiVPAlIaUUpRoFUuBaBZHQFhKYQarFOx1fZQoaAZoCWgPQwjDDfj8MLZJwJSGlFKUaBVLY2gWR0BYTuuieumrdX2UKGgGaAloD0MIw0Xu6epMTMCUhpRSlGgVS0hoFkdAWFTUSZjQRnV9lChoBmgJaA9DCK63zVSIlxjAlIaUUpRoFUtbaBZHQFhWPrfLs8h1fZQoaAZoCWgPQwhsBOJ1/ZhDwJSGlFKUaBVLemgWR0BYV3cgyM1kdX2UKGgGaAloD0MIb2b0o+HURsCUhpRSlGgVS25oFkdAWFf8YQ8OkXV9lChoBmgJaA9DCE28AzxpBVHAlIaUUpRoFUtJaBZHQFhXbgjyFwl1fZQoaAZoCWgPQwgdPX5v039NwJSGlFKUaBVLYmgWR0BYWKNEPUaydX2UKGgGaAloD0MIEfxvJTtmNsCUhpRSlGgVS5hoFkdAWFmXfIjnm3V9lChoBmgJaA9DCCfeAZ60MEjAlIaUUpRoFUttaBZHQFhaNorWiDd1fZQoaAZoCWgPQwgbLQd6qINEwJSGlFKUaBVLbmgWR0BYWrwz+FURdX2UKGgGaAloD0MIZ9MRwM2SKMCUhpRSlGgVS4JoFkdAWFv1h9b5dnV9lChoBmgJaA9DCG03wTdNM2TAlIaUUpRoFUtZaBZHQFhdj8DSw4d1fZQoaAZoCWgPQwjLgLOULEMzwJSGlFKUaBVLh2gWR0BYXsxO+IuXdX2UKGgGaAloD0MIGXYYk/4uLMCUhpRSlGgVS3ZoFkdAWGCUFB6a9nV9lChoBmgJaA9DCMEZ/P1iwFDAlIaUUpRoFUtsaBZHQFhi7+DOC5F1fZQoaAZoCWgPQwjDYtS19khJwJSGlFKUaBVLb2gWR0BYZcsMAmzCdX2UKGgGaAloD0MIEsE4uHR0QMCUhpRSlGgVS1RoFkdAWGlDlYEGJXV9lChoBmgJaA9DCDVdT3RdoE/AlIaUUpRoFUtRaBZHQFhr70nPVut1fZQoaAZoCWgPQwgCSG3i5E5LwJSGlFKUaBVLVGgWR0BYa81baAWjdX2UKGgGaAloD0MIGTigpSvIF8CUhpRSlGgVS1VoFkdAWGvrNW2gF3V9lChoBmgJaA9DCL3faMcNSVTAlIaUUpRoFUtdaBZHQFhul6qsEJV1fZQoaAZoCWgPQwhPeAlOfdZLwJSGlFKUaBVLUWgWR0BYbjXz19ORdX2UKGgGaAloD0MIwVYJFoeQUcCUhpRSlGgVS1poFkdAWG9AC4jKPnV9lChoBmgJaA9DCJS9pZwvfjzAlIaUUpRoFUuHaBZHQFhwo3Jgb6x1fZQoaAZoCWgPQwjnVDIAVKk/wJSGlFKUaBVLZmgWR0BYdrQC0WuYdX2UKGgGaAloD0MIyLYMOEt5IsCUhpRSlGgVS4RoFkdAWHczImw7knV9lChoBmgJaA9DCOzCD86nNFLAlIaUUpRoFUttaBZHQFh28IiTt9h1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 28, "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"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ec9a6c31f852553d46e12c24d5504d084a9b51defb46b348868734556180c27
+size 147287

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.7.0

ppo-LunarLander-v2/data

@@ -0,0 +1,95 @@
+{
+    "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 0x7f8ca0e2f700>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8ca0e2f790>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8ca0e2f820>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8ca0e2f8b0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f8ca0e2f940>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f8ca0e2f9d0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8ca0e2fa60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8ca0e2faf0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f8ca0e2fb80>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8ca0e2fc10>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8ca0e2fca0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8ca0e2fd30>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f8ca0e2a7b0>"
+    },
+    "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": 114688,
+    "_total_timesteps": 100000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1677244227734958693,
+    "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": -0.1468799999999999,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIm1q21pfXYcCUhpRSlIwBbJRLiIwBdJRHQFfLhZha1Tl1fZQoaAZoCWgPQwj8UdSZe/ddwJSGlFKUaBVLf2gWR0BXzkPtlZoxdX2UKGgGaAloD0MIsMqFyr/uIsCUhpRSlGgVS05oFkdAV83m+0w8GXV9lChoBmgJaA9DCP+xEB0CylzAlIaUUpRoFUtqaBZHQFfRGH58BuJ1fZQoaAZoCWgPQwiUT49tGWhIwJSGlFKUaBVLVmgWR0BX0hNVR1oydX2UKGgGaAloD0MItFVJZB+wPECUhpRSlGgVS21oFkdAV9MMLF4s3HV9lChoBmgJaA9DCN82UyEeCTnAlIaUUpRoFUuHaBZHQFfXxASnLq51fZQoaAZoCWgPQwiFsBpLWOc/wJSGlFKUaBVLkWgWR0BX2AOJ+DvmdX2UKGgGaAloD0MIlBPtKqQeR8CUhpRSlGgVS1NoFkdAV9gpUgjhUHV9lChoBmgJaA9DCOdUMgBUZUfAlIaUUpRoFUtZaBZHQFfad3B55Z91fZQoaAZoCWgPQwioiqn0E842wJSGlFKUaBVLWGgWR0BX4NHhCMP0dX2UKGgGaAloD0MIzse1oWKUM8CUhpRSlGgVS3ZoFkdAV+E3cYZVGXV9lChoBmgJaA9DCErRyr3AY1bAlIaUUpRoFUtqaBZHQFfhNdZ7ojh1fZQoaAZoCWgPQwhYWdsUjwtAQJSGlFKUaBVLcmgWR0BX4rCrLhaUdX2UKGgGaAloD0MIXMr5Yu+fT8CUhpRSlGgVS25oFkdAV+JnRLK3eHV9lChoBmgJaA9DCKqB5nPuvifAlIaUUpRoFUt/aBZHQFfmlnyup0h1fZQoaAZoCWgPQwh0QuigS3JewJSGlFKUaBVLg2gWR0BX5v/JeVs2dX2UKGgGaAloD0MIIm3jT1RwSMCUhpRSlGgVS1toFkdAV+inxaxHG3V9lChoBmgJaA9DCBsN4C2QOD/AlIaUUpRoFUtzaBZHQFfqJFb3XZp1fZQoaAZoCWgPQwhj1SDM7UduwJSGlFKUaBVLfmgWR0BX7VDF6zE8dX2UKGgGaAloD0MIzTrj++IOMMCUhpRSlGgVS1loFkdAV+4Nx2jfvXV9lChoBmgJaA9DCKg2OBH9/krAlIaUUpRoFUt6aBZHQFfvUWl/H5t1fZQoaAZoCWgPQwj76T9rfvQ9wJSGlFKUaBVLfGgWR0BX8dXxOLzgdX2UKGgGaAloD0MIYVPnUfEKUMCUhpRSlGgVS2poFkdAV/LPw/gR9XV9lChoBmgJaA9DCE1oklhSQFDAlIaUUpRoFUtUaBZHQFf2Tvy9VWF1fZQoaAZoCWgPQwgjFFtB085OwJSGlFKUaBVLbGgWR0BX/SR8twrEdX2UKGgGaAloD0MIVFbT9US7RsCUhpRSlGgVS2xoFkdAV/0hvBJqZnV9lChoBmgJaA9DCBaiQ+BIlkrAlIaUUpRoFUuGaBZHQFf82ZiNKiB1fZQoaAZoCWgPQwjrAIi7epNOwJSGlFKUaBVLlmgWR0BX/lndweeWdX2UKGgGaAloD0MIGhnkLsIoU8CUhpRSlGgVS2RoFkdAWALim2sq8XV9lChoBmgJaA9DCNb8+EuLahfAlIaUUpRoFUtOaBZHQFgEJemelKt1fZQoaAZoCWgPQwhrfZHQllJbwJSGlFKUaBVLamgWR0BYBggX/HYIdX2UKGgGaAloD0MI0ZSdflD3MMCUhpRSlGgVS45oFkdAWAfIDHOryXV9lChoBmgJaA9DCNF3t7JEOzPAlIaUUpRoFUuRaBZHQFgIRxcVxjt1fZQoaAZoCWgPQwiQFmcMczZFwJSGlFKUaBVLhGgWR0BYCZJPIn0DdX2UKGgGaAloD0MIBD3UtmF+ScCUhpRSlGgVS4doFkdAWAoGOdXkpHV9lChoBmgJaA9DCOBm8WJhKB7AlIaUUpRoFUtgaBZHQFgL5mRNh3J1fZQoaAZoCWgPQwjEeqNWmChQwJSGlFKUaBVLdGgWR0BYDHH/95yEdX2UKGgGaAloD0MILQsm/igQQcCUhpRSlGgVS4toFkdAWBErK/20zHV9lChoBmgJaA9DCDmZuFUQ90vAlIaUUpRoFUuCaBZHQFgTb+tKZlZ1fZQoaAZoCWgPQwgWTtL8MVVIwJSGlFKUaBVLXWgWR0BYFLPdEb5udX2UKGgGaAloD0MINCxGXWvvFcCUhpRSlGgVS2NoFkdAWBYsAeaKDXV9lChoBmgJaA9DCLXhsDTw0UPAlIaUUpRoFUuLaBZHQFgZ6E8JUo91fZQoaAZoCWgPQwi9qUiFsXNIwJSGlFKUaBVLYmgWR0BYHOs5n13/dX2UKGgGaAloD0MIAOFDiZb4VMCUhpRSlGgVS2poFkdAWB3frKNhmXV9lChoBmgJaA9DCHl5OleUNFLAlIaUUpRoFUtYaBZHQFgeksz2vjh1fZQoaAZoCWgPQwhVoBaDh4kOwJSGlFKUaBVLV2gWR0BYICCWeHzpdX2UKGgGaAloD0MIyGDFqdZaN8CUhpRSlGgVS1ZoFkdAWCIQyylennV9lChoBmgJaA9DCBISaRt/8VLAlIaUUpRoFUtXaBZHQFgi1schkiF1fZQoaAZoCWgPQwjku5S6ZPhMwJSGlFKUaBVLkWgWR0BYIlHavicYdX2UKGgGaAloD0MIInGPpQ+VRMCUhpRSlGgVS3FoFkdAWCReu3c583V9lChoBmgJaA9DCBSVDWsqdlTAlIaUUpRoFUudaBZHQFgmTkyULUl1fZQoaAZoCWgPQwjzkCkfglJSwJSGlFKUaBVLgmgWR0BYJqveP7vYdX2UKGgGaAloD0MItoKmJVaqTMCUhpRSlGgVS39oFkdAWCkaOxSpBHV9lChoBmgJaA9DCKyPh767uT/AlIaUUpRoFUtQaBZHQFgo/MGHHm11fZQoaAZoCWgPQwitFthjIqhSwJSGlFKUaBVLW2gWR0BYKk9yLhrFdX2UKGgGaAloD0MI8wAW+fVzFsCUhpRSlGgVS11oFkdAWC0ZIg/1QXV9lChoBmgJaA9DCIv6JHfYtCbAlIaUUpRoFUtPaBZHQFgyWbwz+FV1fZQoaAZoCWgPQwiaJJaUu7RUwJSGlFKUaBVLZWgWR0BYNoLLIPsidX2UKGgGaAloD0MIgJ9x4UD+R8CUhpRSlGgVS55oFkdAWDjoSteUp3V9lChoBmgJaA9DCKFMo8nF7EDAlIaUUpRoFUt1aBZHQFg7YpDu0C11fZQoaAZoCWgPQwj1oKAUrVzkv5SGlFKUaBVLaWgWR0BYPIBJZntfdX2UKGgGaAloD0MIF4BG6dJjT8CUhpRSlGgVS1xoFkdAWD02WIGhVXV9lChoBmgJaA9DCPs9sU6VPUfAlIaUUpRoFUtXaBZHQFg+6QeV9nd1fZQoaAZoCWgPQwhcOuY8Y6tKwJSGlFKUaBVLiWgWR0BYP0QwsXizdX2UKGgGaAloD0MIAWiULv2PNcCUhpRSlGgVS5doFkdAWEAvIwM6R3V9lChoBmgJaA9DCEt1AS8zP1LAlIaUUpRoFUt5aBZHQFg/9ic5Ke11fZQoaAZoCWgPQwgVjbW/swxRwJSGlFKUaBVLaWgWR0BYQ3s9jgAIdX2UKGgGaAloD0MIueAM/n6lT8CUhpRSlGgVS4ZoFkdAWENBQemvXHV9lChoBmgJaA9DCNvEyf0OvUPAlIaUUpRoFUt6aBZHQFhE+8oQWep1fZQoaAZoCWgPQwjLoUW282U5wJSGlFKUaBVLZmgWR0BYRv91loUSdX2UKGgGaAloD0MI8Irgfys7R8CUhpRSlGgVS5JoFkdAWEgQtjCpFXV9lChoBmgJaA9DCBu8r8qFiVPAlIaUUpRoFUuBaBZHQFhKYQarFOx1fZQoaAZoCWgPQwjDDfj8MLZJwJSGlFKUaBVLY2gWR0BYTuuieumrdX2UKGgGaAloD0MIw0Xu6epMTMCUhpRSlGgVS0hoFkdAWFTUSZjQRnV9lChoBmgJaA9DCK63zVSIlxjAlIaUUpRoFUtbaBZHQFhWPrfLs8h1fZQoaAZoCWgPQwhsBOJ1/ZhDwJSGlFKUaBVLemgWR0BYV3cgyM1kdX2UKGgGaAloD0MIb2b0o+HURsCUhpRSlGgVS25oFkdAWFf8YQ8OkXV9lChoBmgJaA9DCE28AzxpBVHAlIaUUpRoFUtJaBZHQFhXbgjyFwl1fZQoaAZoCWgPQwgdPX5v039NwJSGlFKUaBVLYmgWR0BYWKNEPUaydX2UKGgGaAloD0MIEfxvJTtmNsCUhpRSlGgVS5hoFkdAWFmXfIjnm3V9lChoBmgJaA9DCCfeAZ60MEjAlIaUUpRoFUttaBZHQFhaNorWiDd1fZQoaAZoCWgPQwgbLQd6qINEwJSGlFKUaBVLbmgWR0BYWrwz+FURdX2UKGgGaAloD0MIZ9MRwM2SKMCUhpRSlGgVS4JoFkdAWFv1h9b5dnV9lChoBmgJaA9DCG03wTdNM2TAlIaUUpRoFUtZaBZHQFhdj8DSw4d1fZQoaAZoCWgPQwjLgLOULEMzwJSGlFKUaBVLh2gWR0BYXsxO+IuXdX2UKGgGaAloD0MIGXYYk/4uLMCUhpRSlGgVS3ZoFkdAWGCUFB6a9nV9lChoBmgJaA9DCMEZ/P1iwFDAlIaUUpRoFUtsaBZHQFhi7+DOC5F1fZQoaAZoCWgPQwjDYtS19khJwJSGlFKUaBVLb2gWR0BYZcsMAmzCdX2UKGgGaAloD0MIEsE4uHR0QMCUhpRSlGgVS1RoFkdAWGlDlYEGJXV9lChoBmgJaA9DCDVdT3RdoE/AlIaUUpRoFUtRaBZHQFhr70nPVut1fZQoaAZoCWgPQwgCSG3i5E5LwJSGlFKUaBVLVGgWR0BYa81baAWjdX2UKGgGaAloD0MIGTigpSvIF8CUhpRSlGgVS1VoFkdAWGvrNW2gF3V9lChoBmgJaA9DCL3faMcNSVTAlIaUUpRoFUtdaBZHQFhul6qsEJV1fZQoaAZoCWgPQwhPeAlOfdZLwJSGlFKUaBVLUWgWR0BYbjXz19ORdX2UKGgGaAloD0MIwVYJFoeQUcCUhpRSlGgVS1poFkdAWG9AC4jKPnV9lChoBmgJaA9DCJS9pZwvfjzAlIaUUpRoFUuHaBZHQFhwo3Jgb6x1fZQoaAZoCWgPQwjnVDIAVKk/wJSGlFKUaBVLZmgWR0BYdrQC0WuYdX2UKGgGaAloD0MIyLYMOEt5IsCUhpRSlGgVS4RoFkdAWHczImw7knV9lChoBmgJaA9DCOzCD86nNFLAlIaUUpRoFUttaBZHQFh28IiTt9h1ZS4="
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 28,
+    "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
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d85c6d5d8861f26af6633a40d3eab75cef6eff781b99719d4d74ba2fb178c0e0
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:951ca16e06b661bf9b1cd12c77878f9d3dbf01d1e5392c3eea53a43819ecf5a9
+size 43393

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,7 @@
+- 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

results.json

@@ -0,0 +1 @@
+{"mean_reward": -192.92242339641672, "std_reward": 58.22715956762167, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-24T13:12:02.722715"}