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: 68.28 +/- 110.38
+      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 0x7ff9dd066b00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff9dd066b90>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff9dd066c20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff9dd066cb0>", "_build": "<function ActorCriticPolicy._build at 0x7ff9dd066d40>", "forward": "<function ActorCriticPolicy.forward at 0x7ff9dd066dd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff9dd066e60>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff9dd066ef0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff9dd066f80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff9dcfea050>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff9dcfea0e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff9dd0385a0>"}, "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": 1658838017.6147532, "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:": "gAWVfRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIdcsO8Q8XXkCUhpRSlIwBbJRN6AOMAXSUR0CTvN4cFQl9dX2UKGgGaAloD0MIwxGkUuwQP0CUhpRSlGgVTegDaBZHQJO+m+8Gs3h1fZQoaAZoCWgPQwhAvRk1X6dQQJSGlFKUaBVN6ANoFkdAk7/I8p1A7nV9lChoBmgJaA9DCHIW9rTDUVpAlIaUUpRoFU3oA2gWR0CTwW7RfF72dX2UKGgGaAloD0MIrcCQ1a3pUECUhpRSlGgVTegDaBZHQJPF+MuOCGx1fZQoaAZoCWgPQwi0sKcd/gY7QJSGlFKUaBVN6ANoFkdAk8bl+NLlFXV9lChoBmgJaA9DCOZXc4BgJ1dAlIaUUpRoFU3oA2gWR0CTxysU7CBPdX2UKGgGaAloD0MICMxDpnyGScCUhpRSlGgVTRgBaBZHQJPLbe54GEB1fZQoaAZoCWgPQwj0cALTacZVQJSGlFKUaBVN6ANoFkdAk8vbgbZOBXV9lChoBmgJaA9DCN1hE5m5ekvAlIaUUpRoFU0/AWgWR0CTzhDklu3udX2UKGgGaAloD0MIBTV8C+tQUsCUhpRSlGgVTTsBaBZHQJPPj+Idlup1fZQoaAZoCWgPQwiuZp3xfeEbwJSGlFKUaBVL5mgWR0CT03jxkNF0dX2UKGgGaAloD0MIo1nZPuQtB0CUhpRSlGgVTQABaBZHQJPT//DLr5Z1fZQoaAZoCWgPQwiduByvQPpawJSGlFKUaBVNzgJoFkdAk9X0KzAvc3V9lChoBmgJaA9DCOtwdJXuMVLAlIaUUpRoFU0iAWgWR0CT1z+jua4MdX2UKGgGaAloD0MIzF1LyAeNWUCUhpRSlGgVTegDaBZHQJPfxMyrPt51fZQoaAZoCWgPQwjOjekJS6BYQJSGlFKUaBVN6ANoFkdAk+BsZ5zHTHV9lChoBmgJaA9DCK8GKA01sFLAlIaUUpRoFU18AWgWR0CT5WlIVdondX2UKGgGaAloD0MIptB5jV26S8CUhpRSlGgVTUABaBZHQJPoIyzolld1fZQoaAZoCWgPQwi94T5ya55bQJSGlFKUaBVN6ANoFkdAk/2T8cdYGXV9lChoBmgJaA9DCIp0P6cgK0lAlIaUUpRoFU3oA2gWR0CT/aWRRuTBdX2UKGgGaAloD0MIOSo3UUuzHMCUhpRSlGgVTVQBaBZHQJQAbYf4h2Z1fZQoaAZoCWgPQwhQ4978hqpVQJSGlFKUaBVN6ANoFkdAlAKC0Sh8IHV9lChoBmgJaA9DCPrt68A5JWPAlIaUUpRoFU2tAWgWR0CUAof7rLQpdX2UKGgGaAloD0MI0TyARX75WECUhpRSlGgVTegDaBZHQJQGehM8HOd1fZQoaAZoCWgPQwgra5vicSEoQJSGlFKUaBVL/WgWR0CUDPW9DhLodX2UKGgGaAloD0MIzcth9x1DCkCUhpRSlGgVTegDaBZHQJQOY0m+j/N1fZQoaAZoCWgPQwgjLgCN0jxVQJSGlFKUaBVN6ANoFkdAlBBgnpjc23V9lChoBmgJaA9DCNApyM9Grtu/lIaUUpRoFU1hAWgWR0CUEKqxC6YmdX2UKGgGaAloD0MI/x8nTBi3SsCUhpRSlGgVTScBaBZHQJQUMnF5v991fZQoaAZoCWgPQwinXOFdLttRQJSGlFKUaBVN6ANoFkdAlBxiQtBfKXV9lChoBmgJaA9DCBUeNLvuklpAlIaUUpRoFU3oA2gWR0CUHOB2fTTfdX2UKGgGaAloD0MINLqD2JnC57+UhpRSlGgVTegDaBZHQJQhWUGFBY51fZQoaAZoCWgPQwgUz9kCQkVCwJSGlFKUaBVNUwFoFkdAlCcRqTKT0XV9lChoBmgJaA9DCAhW1cvv/VdAlIaUUpRoFU3oA2gWR0CUKVDmbLEDdX2UKGgGaAloD0MIvCTOiqg7QMCUhpRSlGgVTT0BaBZHQJQpxm9QGfR1fZQoaAZoCWgPQwhmTMEaZ/ZdQJSGlFKUaBVN3QNoFkdAlDQdZFG5MHV9lChoBmgJaA9DCBVwz/OntTRAlIaUUpRoFU3oA2gWR0CUNDXgLqlhdX2UKGgGaAloD0MIO6dZoN2sWkCUhpRSlGgVTegDaBZHQJQ6VlI3BHl1fZQoaAZoCWgPQwihFK3cC2lRwJSGlFKUaBVNHwFoFkdAlD4TuSfUWnV9lChoBmgJaA9DCBoziXpB4GJAlIaUUpRoFU3iAmgWR0CUP8tthuwYdX2UKGgGaAloD0MIiqvKvis4VUCUhpRSlGgVTegDaBZHQJRAckC3gDR1fZQoaAZoCWgPQwjItaFinCdRQJSGlFKUaBVN6ANoFkdAlFZo5PuXu3V9lChoBmgJaA9DCDIiUWhZbV9AlIaUUpRoFU3oA2gWR0CUWLLR8c+8dX2UKGgGaAloD0MIJnFWRE00SMCUhpRSlGgVTR0BaBZHQJRbmgQHzH11fZQoaAZoCWgPQwgF+G7zRtVgQJSGlFKUaBVN6ANoFkdAlF1CUornT3V9lChoBmgJaA9DCO8dNSbEDCzAlIaUUpRoFU1TAWgWR0CUZNDQqqffdX2UKGgGaAloD0MICYofY+6zX0CUhpRSlGgVTegDaBZHQJRl4FlkH2R1fZQoaAZoCWgPQwjC+j+H+blSQJSGlFKUaBVN6ANoFkdAlGge2qkuYnV9lChoBmgJaA9DCCUFFsCU8FfAlIaUUpRoFU3WA2gWR0CUdF2pAD7qdX2UKGgGaAloD0MIINJvXwf0X0CUhpRSlGgVTegDaBZHQJR2V/4Irvt1fZQoaAZoCWgPQwgbDeAtkORIQJSGlFKUaBVN6ANoFkdAlHtg6QvHtHV9lChoBmgJaA9DCI4CRMGMPVhAlIaUUpRoFU3oA2gWR0CUgWWnCO3ldX2UKGgGaAloD0MIuycPC7UdW0CUhpRSlGgVTegDaBZHQJSEFu0kWyl1fZQoaAZoCWgPQwhuMT83NKdbQJSGlFKUaBVN6ANoFkdAlI6RXOnl4nV9lChoBmgJaA9DCOkq3V1nwGRAlIaUUpRoFU2WAWgWR0CUkbyo4uK5dX2UKGgGaAloD0MIDFhyFYu/BcCUhpRSlGgVS/VoFkdAlJK/ywwCbXV9lChoBmgJaA9DCPBquTMTaV5AlIaUUpRoFU3oA2gWR0CUl/YjSofkdX2UKGgGaAloD0MI4ZhlTwKKV0CUhpRSlGgVTegDaBZHQJSZiPaL4vh1fZQoaAZoCWgPQwhwl/2601liQJSGlFKUaBVN6ANoFkdAlJoVBt1p03V9lChoBmgJaA9DCNMyUu+puFhAlIaUUpRoFU3oA2gWR0CUr59QGfPHdX2UKGgGaAloD0MIfxMKEXD+R0CUhpRSlGgVTegDaBZHQJSxj4DcM3J1fZQoaAZoCWgPQwiwyK8fYvtXQJSGlFKUaBVN6ANoFkdAlLQyWzF+/nV9lChoBmgJaA9DCJXzxd6L31hAlIaUUpRoFU3oA2gWR0CUtasRxtHhdX2UKGgGaAloD0MIxD9s6dFcMkCUhpRSlGgVTU4BaBZHQJS3GCPIXCV1fZQoaAZoCWgPQwgZ6NoX0J5aQJSGlFKUaBVN6ANoFkdAlLw6QRwqAnV9lChoBmgJaA9DCC3r/rEQv2BAlIaUUpRoFU3oA2gWR0CUvSVinYQKdX2UKGgGaAloD0MILJ0PzxKXU0CUhpRSlGgVTegDaBZHQJS/C8g6ltV1fZQoaAZoCWgPQwgipdk8DgxVQJSGlFKUaBVN6ANoFkdAlMt0CJXQt3V9lChoBmgJaA9DCCHmkqrtckLAlIaUUpRoFU0BAWgWR0CUzcCkoF3ZdX2UKGgGaAloD0MIsOO/QBCwTUCUhpRSlGgVTegDaBZHQJTQPjLjght1fZQoaAZoCWgPQwinsFJBRdXzv5SGlFKUaBVNVgFoFkdAlNKEM1CPZXV9lChoBmgJaA9DCD5d3bHYxi5AlIaUUpRoFU0vAWgWR0CU0wzz3AVPdX2UKGgGaAloD0MIzojS3uBZYECUhpRSlGgVTfQCaBZHQJTUxXhfjS51fZQoaAZoCWgPQwhjRnh7EJJZQJSGlFKUaBVN6ANoFkdAlNgJUHY6GXV9lChoBmgJaA9DCJdTAmISQjjAlIaUUpRoFUv3aBZHQJTits67ulZ1fZQoaAZoCWgPQwgF3zR9dnlVQJSGlFKUaBVN6ANoFkdAlOZXb/Ot4nV9lChoBmgJaA9DCA6Fz9ZBRGFAlIaUUpRoFU3oA2gWR0CU69vnKW9ldX2UKGgGaAloD0MIcnDpmPPKX0CUhpRSlGgVTegDaBZHQJTtecG1QZZ1fZQoaAZoCWgPQwgPKQZINBBdQJSGlFKUaBVN6ANoFkdAlO4DLr5ZbXV9lChoBmgJaA9DCHcv98lRG1xAlIaUUpRoFU3oA2gWR0CU8OGi5/b1dX2UKGgGaAloD0MI5BWInhStYECUhpRSlGgVTegDaBZHQJUFwZxaPjp1fZQoaAZoCWgPQwiO6QlLPKVgQJSGlFKUaBVN6ANoFkdAlQh8mF8G93V9lChoBmgJaA9DCG5Q+62dl1tAlIaUUpRoFU3oA2gWR0CVCeat9x6wdX2UKGgGaAloD0MI7rCJzFxJZkCUhpRSlGgVTegDaBZHQJULSGgzxgB1fZQoaAZoCWgPQwhgWWlSCrokQJSGlFKUaBVNIwFoFkdAlRJ3S8an8HV9lChoBmgJaA9DCF03pbxWZFxAlIaUUpRoFU3oA2gWR0CVIi5ooNNKdX2UKGgGaAloD0MIWriswubbYkCUhpRSlGgVTegDaBZHQJUko6CDmKZ1fZQoaAZoCWgPQwhrm+Jx0QthQJSGlFKUaBVN6ANoFkdAlScVl9SdfHV9lChoBmgJaA9DCKPMBpnkzGNAlIaUUpRoFU3oA2gWR0CVKbby6MBIdX2UKGgGaAloD0MIJLTlXIr5WkCUhpRSlGgVTegDaBZHQJUrQmZ3LV51fZQoaAZoCWgPQwiKARJNIANhQJSGlFKUaBVN6ANoFkdAlS4Rx95Qg3V9lChoBmgJaA9DCGlU4GQbCWpAlIaUUpRoFU1tAmgWR0CVM8iHIp6QdX2UKGgGaAloD0MIrwj+txIXYUCUhpRSlGgVTegDaBZHQJU3JRiw0O51fZQoaAZoCWgPQwhT7Ggc6pFoQJSGlFKUaBVNMgJoFkdAlTdUUj9n9XV9lChoBmgJaA9DCGH+CpkraVtAlIaUUpRoFU3oA2gWR0CVOf7KaG5+dX2UKGgGaAloD0MImpguxOpGW0CUhpRSlGgVTegDaBZHQJU+i+cpb2V1fZQoaAZoCWgPQwhksOJU66thQJSGlFKUaBVN6ANoFkdAlT/i3w1BMXV9lChoBmgJaA9DCLitLTwvz0pAlIaUUpRoFU3oA2gWR0CVQwciW3SbdX2UKGgGaAloD0MIIhtIF5u3YECUhpRSlGgVTegDaBZHQJVFBsKsuFp1ZS4="}, "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-5.4.188+-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.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e30eb5f68798a0983737000eaea43214f5357e27f9f5616eb884713a1e80102d
+size 147140

ppo-LunarLander-v2/_stable_baselines3_version

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

ppo-LunarLander-v2/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 0x7ff9dd066b00>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff9dd066b90>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff9dd066c20>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff9dd066cb0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ff9dd066d40>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ff9dd066dd0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff9dd066e60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ff9dd066ef0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff9dd066f80>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff9dcfea050>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff9dcfea0e0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7ff9dd0385a0>"
+    },
+    "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": 1658838017.6147532,
+    "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:": "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"
+    },
+    "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
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6d88f3cec30d35e262114347ebec08508db906fd841d66aaa31a94063a633d2e
+size 87865

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:63667b281f62699a382d77527ed5c1565322b5d59e52f8951bbb243430c14ac8
+size 43201

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-5.4.188+-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": 68.28065552198909, "std_reward": 110.37649706668509, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-26T12:44:24.329993"}