Upload PPO LunarLander-v2 trained agent

README.md

@@ -0,0 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 192.73 +/- 68.64
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+# **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 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 0x7fe5b7715950>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe5b77159e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe5b7715a70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe5b7715b00>", "_build": "<function ActorCriticPolicy._build at 0x7fe5b7715b90>", "forward": "<function ActorCriticPolicy.forward at 0x7fe5b7715c20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe5b7715cb0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fe5b7715d40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe5b7715dd0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe5b7715e60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe5b7715ef0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fe5b77608a0>"}, "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": 1658567620.824597, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVfhAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIbLJGPUSDXUCUhpRSlIwBbJRN6AOMAXSUR0CRPhmNR3vAdX2UKGgGaAloD0MI0T3rGi0eWUCUhpRSlGgVTegDaBZHQJE+iRT0g8t1fZQoaAZoCWgPQwgQyZBj67JZQJSGlFKUaBVN6ANoFkdAkT7s+eOGTXV9lChoBmgJaA9DCOTziqceXFJAlIaUUpRoFU3oA2gWR0CRSdTWXkYGdX2UKGgGaAloD0MIO4kI/yLBUUCUhpRSlGgVTegDaBZHQJFLwGZ/kNp1fZQoaAZoCWgPQwi+FB40O/diQJSGlFKUaBVN6ANoFkdAkU0eAI6bOXV9lChoBmgJaA9DCGyvBb23B2RAlIaUUpRoFU3oA2gWR0CRTkAZsKsudX2UKGgGaAloD0MI7fXuj/exWECUhpRSlGgVTegDaBZHQJFO/VXmvGJ1fZQoaAZoCWgPQwhIUPwYcx1VQJSGlFKUaBVN6ANoFkdAkWTTTa0x/XV9lChoBmgJaA9DCM8Tz9kCC1lAlIaUUpRoFU3oA2gWR0CRZY4wAU+LdX2UKGgGaAloD0MIWYY41sXfXkCUhpRSlGgVTegDaBZHQJFlnHcUM5R1fZQoaAZoCWgPQwgYYB+duphcQJSGlFKUaBVN6ANoFkdAkWeX8GcFyXV9lChoBmgJaA9DCBXgu80bC0xAlIaUUpRoFU3oA2gWR0CRb8fW+XZ5dX2UKGgGaAloD0MIeCY0SSwXXkCUhpRSlGgVTegDaBZHQJF11yp71I11fZQoaAZoCWgPQwg2ct2U8vpjQJSGlFKUaBVN6ANoFkdAkXX52ECeVnV9lChoBmgJaA9DCE64V+atpmJAlIaUUpRoFU3oA2gWR0CRecMQEpy7dX2UKGgGaAloD0MIEHaKVYMFYkCUhpRSlGgVTegDaBZHQJGR+tFKCg91fZQoaAZoCWgPQwirWWd8X0NUQJSGlFKUaBVN6ANoFkdAkZJ8zyjHn3V9lChoBmgJaA9DCE1Iawy69GFAlIaUUpRoFU3oA2gWR0CRkvH3lCC0dX2UKGgGaAloD0MIKSDtf4CGW0CUhpRSlGgVTegDaBZHQJGfgIw/PgN1fZQoaAZoCWgPQwiZEHNJ1TlaQJSGlFKUaBVN6ANoFkdAkaHUMPSUknV9lChoBmgJaA9DCAR1yqMb3llAlIaUUpRoFU3oA2gWR0CRo45hScbzdX2UKGgGaAloD0MIw0fElEhdXkCUhpRSlGgVTegDaBZHQJGk90YCQtB1fZQoaAZoCWgPQwgsRIfAkUpcQJSGlFKUaBVN6ANoFkdAkaXJ48lolHV9lChoBmgJaA9DCL4vLlXpCWBAlIaUUpRoFU3oA2gWR0CRvFWac7QtdX2UKGgGaAloD0MIhq+vdal6XECUhpRSlGgVTegDaBZHQJG9RKBd2Pl1fZQoaAZoCWgPQwhTBDi9iwVaQJSGlFKUaBVN6ANoFkdAkb1WJN0vG3V9lChoBmgJaA9DCDKuuDgqa1xAlIaUUpRoFU3oA2gWR0CRv/YPXkHVdX2UKGgGaAloD0MIZAW/DTHoX0CUhpRSlGgVTegDaBZHQJHLG6ErXlN1fZQoaAZoCWgPQwhrEVFM3mAvwJSGlFKUaBVNdgFoFkdAkcweeJ53T3V9lChoBmgJaA9DCFeXUwJiqENAlIaUUpRoFUvnaBZHQJHQIl8gIQh1fZQoaAZoCWgPQwg9uhEWFV9bQJSGlFKUaBVN6ANoFkdAkdH4RqXWv3V9lChoBmgJaA9DCIulSL4SbFtAlIaUUpRoFU3oA2gWR0CR0hwOvt+kdX2UKGgGaAloD0MIxoZu9gf2M8CUhpRSlGgVTUIBaBZHQJHSYxGlQ/J1fZQoaAZoCWgPQwiKy/EKRM9iQJSGlFKUaBVN6ANoFkdAkdXI9xIatXV9lChoBmgJaA9DCB/2QgHbg15AlIaUUpRoFU3oA2gWR0CR6+YNiH6/dX2UKGgGaAloD0MI1jkGZK9wXkCUhpRSlGgVTegDaBZHQJHsaCOFQEZ1fZQoaAZoCWgPQwiuK2aEtzheQJSGlFKUaBVN6ANoFkdAkezWzWwu/XV9lChoBmgJaA9DCDdStkjaY2BAlIaUUpRoFU3oA2gWR0CR+piCrcTKdX2UKGgGaAloD0MIN8ZOeAmYSECUhpRSlGgVTegDaBZHQJH8Nw3o9s91fZQoaAZoCWgPQwiNYrml1e5eQJSGlFKUaBVN6ANoFkdAkf2Km4y44XV9lChoBmgJaA9DCCld+pekn15AlIaUUpRoFU3oA2gWR0CR/m3YcvM9dX2UKGgGaAloD0MI9KYiFcYGJkCUhpRSlGgVTQoBaBZHQJH/jv2GqPx1fZQoaAZoCWgPQwiKsOHplatjQJSGlFKUaBVN6ANoFkdAkgLFtoBaLXV9lChoBmgJaA9DCKM6Hch6Sg5AlIaUUpRoFU3oA2gWR0CSAtaGpMpPdX2UKGgGaAloD0MIIgA49uwpQMCUhpRSlGgVS9doFkdAkhqMo+fRNXV9lChoBmgJaA9DCCaPp+UH3hHAlIaUUpRoFUv/aBZHQJIeJvegte51fZQoaAZoCWgPQwjQmbSpuvhaQJSGlFKUaBVN6ANoFkdAkiGYK6WgOHV9lChoBmgJaA9DCCO6Z12jQlxAlIaUUpRoFU3oA2gWR0CSInc/MW43dX2UKGgGaAloD0MI7Q+U2/YGVUCUhpRSlGgVTegDaBZHQJIldCBwuNB1fZQoaAZoCWgPQwgboDTUKCRYQJSGlFKUaBVN6ANoFkdAkibYldC3PXV9lChoBmgJaA9DCIz1DUxutWJAlIaUUpRoFU3oA2gWR0CSJvPPszEadX2UKGgGaAloD0MI7Uj1nV9xV0CUhpRSlGgVTegDaBZHQJInKyVv/BF1fZQoaAZoCWgPQwhbs5WX/NZZQJSGlFKUaBVN6ANoFkdAkimXxri2lXV9lChoBmgJaA9DCHUEcLP4lGdAlIaUUpRoFU3bAWgWR0CSLw0Kqn3tdX2UKGgGaAloD0MIp1mg3aG6YECUhpRSlGgVTegDaBZHQJI8T3ai9Ix1fZQoaAZoCWgPQwijdVQ1QXJoQJSGlFKUaBVNhAFoFkdAkjx60IC2dHV9lChoBmgJaA9DCI1BJ4QO1FxAlIaUUpRoFU3oA2gWR0CSPKunuRcNdX2UKGgGaAloD0MIHa7VHvbcUkCUhpRSlGgVTegDaBZHQJJL2FfzBhx1fZQoaAZoCWgPQwjH2XQEcHdfQJSGlFKUaBVN6ANoFkdAkkyzgMtsenV9lChoBmgJaA9DCMh4lEp4M1FAlIaUUpRoFU3oA2gWR0CSTeYR/ViGdX2UKGgGaAloD0MIBHKJIw+2YUCUhpRSlGgVTegDaBZHQJJRI7HQyAR1fZQoaAZoCWgPQwhgArfu5oNiQJSGlFKUaBVN6ANoFkdAkmoihN/OMXV9lChoBmgJaA9DCMv3jEToz2BAlIaUUpRoFU3oA2gWR0CSbf0uUUwjdX2UKGgGaAloD0MIAd9t3jgiYUCUhpRSlGgVTegDaBZHQJJxfILgGbF1fZQoaAZoCWgPQwhAwjBgyZ5eQJSGlFKUaBVN6ANoFkdAknJfCAMDwHV9lChoBmgJaA9DCEz/klSmOFdAlIaUUpRoFU3oA2gWR0CSdb9kjHGTdX2UKGgGaAloD0MI9gt2wzZtY0CUhpRSlGgVTegDaBZHQJJ35RUFSsN1fZQoaAZoCWgPQwiUTiSYan5dQJSGlFKUaBVN6ANoFkdAknhGrsByS3V9lChoBmgJaA9DCEikbfyJQ1tAlIaUUpRoFU3oA2gWR0CSfIyd4FA3dX2UKGgGaAloD0MI7+U+OYomYECUhpRSlGgVTegDaBZHQJKDpMdtEXt1fZQoaAZoCWgPQwhDxw4qcatEwJSGlFKUaBVNLwFoFkdAkpBZwfhddHV9lChoBmgJaA9DCB+94T5yXmFAlIaUUpRoFU3oA2gWR0CSkgvhIe5ndX2UKGgGaAloD0MIEJaxoZt0YUCUhpRSlGgVTegDaBZHQJKSNKCg9Nh1fZQoaAZoCWgPQwj3x3vVytVdQJSGlFKUaBVN6ANoFkdAkpJqGL1mJ3V9lChoBmgJaA9DCG0CDMufdy9AlIaUUpRoFU0mAWgWR0CSl2ARChN/dX2UKGgGaAloD0MI7NtJRPjNW0CUhpRSlGgVTegDaBZHQJKhSI7/4qR1fZQoaAZoCWgPQwiCdRw/1NRgQJSGlFKUaBVN6ANoFkdAkqIhxo7FKnV9lChoBmgJaA9DCCO/fogNJGJAlIaUUpRoFU3oA2gWR0CSo1iVB2OidX2UKGgGaAloD0MIXcKht3hZXECUhpRSlGgVTegDaBZHQJKmnaCcwxp1fZQoaAZoCWgPQwjzOuKQDQwywJSGlFKUaBVNPgFoFkdAkqdRm5DqnnV9lChoBmgJaA9DCFDgnXx6FWBAlIaUUpRoFU3oA2gWR0CSv2YSQHRkdX2UKGgGaAloD0MI63B0lW44YECUhpRSlGgVTegDaBZHQJLDhxVAAyV1fZQoaAZoCWgPQwhxyAbSxe5fQJSGlFKUaBVN6ANoFkdAksc6naWX1XV9lChoBmgJaA9DCDHT9q+sll9AlIaUUpRoFU3oA2gWR0CSyCd6cAindX2UKGgGaAloD0MIXknyXN8PYkCUhpRSlGgVTegDaBZHQJLLxCF9KEp1fZQoaAZoCWgPQwhwmdNlMWtXQJSGlFKUaBVN6ANoFkdAks1zDCP6sXV9lChoBmgJaA9DCBjMXyFzyl1AlIaUUpRoFU3oA2gWR0CSzbmrKeTWdX2UKGgGaAloD0MINGlTdY8sbUCUhpRSlGgVTe4BaBZHQJLZW7FsHjZ1fZQoaAZoCWgPQwhX6INlbOgywJSGlFKUaBVNHwFoFkdAktlt07r9l3V9lChoBmgJaA9DCFn9EYaBJ2VAlIaUUpRoFU3oA2gWR0CS5e6STyJ9dX2UKGgGaAloD0MI63Hfap01VkCUhpRSlGgVTegDaBZHQJLntDRc/t91fZQoaAZoCWgPQwhd/G1PkKdcQJSGlFKUaBVN6ANoFkdAkufg3cYZVHV9lChoBmgJaA9DCGeBdocUjmJAlIaUUpRoFU3oA2gWR0CS7aIt16mgdX2UKGgGaAloD0MI3q0s0Vl2GMCUhpRSlGgVTSMBaBZHQJLuvT8YQ8R1fZQoaAZoCWgPQwjCFyZThUlgQJSGlFKUaBVN6ANoFkdAkvivszEaVHV9lChoBmgJaA9DCFzJjo1AE2FAlIaUUpRoFU3oA2gWR0CS+aKAJ9iMdX2UKGgGaAloD0MIkJ+NXDdkWUCUhpRSlGgVTegDaBZHQJL6+MFUyYZ1fZQoaAZoCWgPQwg0K9uHvBk0wJSGlFKUaBVNLgFoFkdAkv4VSflIVnV9lChoBmgJaA9DCMfa39keSldAlIaUUpRoFU3oA2gWR0CS/3PFvQ4TdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "n_steps": 1024, "gamma": 0.995, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.6.0", "PyTorch": "1.12.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2-995.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb128f9e04bf0e02b5b7a82689fa1a0536aedf84567f5c0e366c86a95326543d
+size 147139

ppo-LunarLander-v2-995/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.0

ppo-LunarLander-v2-995/data

@@ -0,0 +1,94 @@
+{
+    "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 0x7fe5b7715950>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe5b77159e0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe5b7715a70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe5b7715b00>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fe5b7715b90>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fe5b7715c20>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe5b7715cb0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fe5b7715d40>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe5b7715dd0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe5b7715e60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe5b7715ef0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fe5b77608a0>"
+    },
+    "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": 1658567620.824597,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.015808000000000044,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 124,
+    "n_steps": 1024,
+    "gamma": 0.995,
+    "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-v2-995/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a0f3bc99009d48632a6a34a8b5f13c1ed3d4ed517f69f10bc1a39fe81cde7c00
+size 87865

ppo-LunarLander-v2-995/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:033bc115d34080b59fd9b936f0b9868222428dab45ae4d81925f84711076aedd
+size 43201

ppo-LunarLander-v2-995/pytorch_variables.pth

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

ppo-LunarLander-v2-995/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.6.0
+PyTorch: 1.12.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 192.72926643326497, "std_reward": 68.63546773585838, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-23T09:28:45.942294"}