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: -17.39 +/- 121.33
+      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 0x7fa0b2ea7b90>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa0b2ea7c20>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa0b2ea7cb0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa0b2ea7d40>", "_build": "<function ActorCriticPolicy._build at 0x7fa0b2ea7dd0>", "forward": "<function ActorCriticPolicy.forward at 0x7fa0b2ea7e60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa0b2ea7ef0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fa0b2ea7f80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa0b2e2e050>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa0b2e2e0e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa0b2e2e170>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fa0b2e6dbd0>"}, "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": 1660291219.4428518, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQCUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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////9LAHSUYkMIX5fhP92JUMCUhpRSlIwBbJRLV4wBdJRHQIUgJGBnSOR1fZQoaAZoCWgPQwjdfCO6Z2VVwJSGlFKUaBVLVGgWR0CFICNb1RLsdX2UKGgGaAloD0MIQS5x5IHNXsCUhpRSlGgVS0FoFkdAhSCdsabWmXV9lChoBmgJaA9DCPzepj/7YF3AlIaUUpRoFUtVaBZHQIUgviPyTZB1fZQoaAZoCWgPQwg/cQD9vrVOwJSGlFKUaBVLVWgWR0CFIOBmwqy4dX2UKGgGaAloD0MIGsHG9e99WMCUhpRSlGgVS0hoFkdAhSDqohpxm3V9lChoBmgJaA9DCC7kEdxIFlXAlIaUUpRoFUtOaBZHQIUhf6j32251fZQoaAZoCWgPQwi3nEtxVSZjwJSGlFKUaBVLf2gWR0CFIcF7laKUdX2UKGgGaAloD0MIDFwea0agSsCUhpRSlGgVS2ZoFkdAhSHb/4qPO3V9lChoBmgJaA9DCBZp4h1gj2DAlIaUUpRoFUtYaBZHQIUh7hHbypd1fZQoaAZoCWgPQwiu2cpL/kpUwJSGlFKUaBVLVWgWR0CFIgVY6nzhdX2UKGgGaAloD0MI6pJxjGTsWcCUhpRSlGgVS2RoFkdAhSH9pRGc4HV9lChoBmgJaA9DCPhQoiWPs1XAlIaUUpRoFUtUaBZHQIUiEV8CxNZ1fZQoaAZoCWgPQwiefeVBekI2wJSGlFKUaBVLRGgWR0CFIpUtI066dX2UKGgGaAloD0MI7N0f79XSY8CUhpRSlGgVS1poFkdAhSK0utfXw3V9lChoBmgJaA9DCGWKOQg6GFXAlIaUUpRoFUtlaBZHQIUjDWmP5pJ1fZQoaAZoCWgPQwg+INCZtCFYwJSGlFKUaBVLeGgWR0CFIycFQl8gdX2UKGgGaAloD0MIhNVYwtqMS8CUhpRSlGgVS1JoFkdAhSMpxNqQBHV9lChoBmgJaA9DCDfeHRmrE1fAlIaUUpRoFUt6aBZHQIUjO3F1jiJ1fZQoaAZoCWgPQwjMKmwGuO9XwJSGlFKUaBVLS2gWR0CFI8VNYbKidX2UKGgGaAloD0MIxNFVurt+VcCUhpRSlGgVS19oFkdAhSO9ORDCxnV9lChoBmgJaA9DCFTE6SRbQFnAlIaUUpRoFUtDaBZHQIUj6EHt4Rp1fZQoaAZoCWgPQwg+INCZtNxWwJSGlFKUaBVLQGgWR0CFI+JRfnfVdX2UKGgGaAloD0MIeR9Hc2QKWcCUhpRSlGgVS2poFkdAhSQJe3QUpXV9lChoBmgJaA9DCCFaK9ocqVXAlIaUUpRoFUtOaBZHQIUkYKlYU351fZQoaAZoCWgPQwivITgu48RXwJSGlFKUaBVLVmgWR0CFJF/oaDPGdX2UKGgGaAloD0MI7pi6K7spU8CUhpRSlGgVS1RoFkdAhSUYR/ViF3V9lChoBmgJaA9DCKa6gJcZ7lDAlIaUUpRoFUtqaBZHQIUlPRNRFZx1fZQoaAZoCWgPQwjWAKWhRiFFwJSGlFKUaBVLSGgWR0CFJUzpHI6sdX2UKGgGaAloD0MI28LzUrFsXMCUhpRSlGgVS3ZoFkdAhSWFt8/lhnV9lChoBmgJaA9DCNVamIV2AFLAlIaUUpRoFUu+aBZHQIUltknTiKl1fZQoaAZoCWgPQwiFeCRenv5RwJSGlFKUaBVLRGgWR0CFJebrC3w1dX2UKGgGaAloD0MIy2YOSS0VYMCUhpRSlGgVS2toFkdAhSXumJm/WXV9lChoBmgJaA9DCOPEVzuKMFXAlIaUUpRoFUtPaBZHQIUmI08/2TR1fZQoaAZoCWgPQwjJAbuaPBNIwJSGlFKUaBVLP2gWR0CFJkE4ecQRdX2UKGgGaAloD0MIm+jzUUaaXMCUhpRSlGgVS0xoFkdAhSavCl7+k3V9lChoBmgJaA9DCIgSLXk8bU7AlIaUUpRoFUtkaBZHQIUmxRGc4HZ1fZQoaAZoCWgPQwhM4UGz61NUwJSGlFKUaBVLfGgWR0CFJtMV1wHadX2UKGgGaAloD0MI3nL1Y5OXYMCUhpRSlGgVS2RoFkdAhSbvw/gR9XV9lChoBmgJaA9DCNCAejNqal3AlIaUUpRoFUuCaBZHQIUnFB6a9bp1fZQoaAZoCWgPQwgUkszqHeFbwJSGlFKUaBVLaWgWR0CFJzA4XGfgdX2UKGgGaAloD0MISZ9W0Z8WYMCUhpRSlGgVS4poFkdAhSdeQMhHLHV9lChoBmgJaA9DCNS5opQQJlnAlIaUUpRoFUtMaBZHQIUnhRfnfVJ1fZQoaAZoCWgPQwgvaverABdSwJSGlFKUaBVLXmgWR0CFJ+EjgQ6IdX2UKGgGaAloD0MIkSbeAZ79UcCUhpRSlGgVS0poFkdAhSgUWM0gsHV9lChoBmgJaA9DCKj8a3nlWFXAlIaUUpRoFUtNaBZHQIUoXGVAzHl1fZQoaAZoCWgPQwg4MSQnE2tNwJSGlFKUaBVLaGgWR0CFKI9mHxjKdX2UKGgGaAloD0MI1ESfjzKoUcCUhpRSlGgVSz1oFkdAhSiiOmzjWHV9lChoBmgJaA9DCPmBqzyBiVfAlIaUUpRoFUtzaBZHQIUorGza9K51fZQoaAZoCWgPQwgzFeKReB9VwJSGlFKUaBVLSmgWR0CFKONiH6/JdX2UKGgGaAloD0MInwQ25+ADVcCUhpRSlGgVS0toFkdAhSjfsE7nxXV9lChoBmgJaA9DCO8bX3tmyUnAlIaUUpRoFUtRaBZHQIUo9nAZbY91fZQoaAZoCWgPQwikjLgANBRKwJSGlFKUaBVLcWgWR0CFKQDwpe/pdX2UKGgGaAloD0MIGHyakxdqUcCUhpRSlGgVS3BoFkdAhSki2c8Tz3V9lChoBmgJaA9DCGKga19AylLAlIaUUpRoFUtGaBZHQIUp0zImw7l1fZQoaAZoCWgPQwiSzyueei1UwJSGlFKUaBVLX2gWR0CFKiw1zhgmdX2UKGgGaAloD0MIcXZrmQxLQ8CUhpRSlGgVS29oFkdAhSpKJVKf4HV9lChoBmgJaA9DCFX3yOaqy0jAlIaUUpRoFUuNaBZHQIUqSaEzwc51fZQoaAZoCWgPQwiM8szLYQlGwJSGlFKUaBVLaWgWR0CFKlAzpHI7dX2UKGgGaAloD0MIwTbiyW5lWMCUhpRSlGgVS0loFkdAhSpuP/7zkXV9lChoBmgJaA9DCIMVp1oLUzDAlIaUUpRoFUtDaBZHQIUqheC04R51fZQoaAZoCWgPQwgBLzNslOFYwJSGlFKUaBVLVWgWR0CFKnzZHuqndX2UKGgGaAloD0MIyjLEsS4UXMCUhpRSlGgVS31oFkdAhSqW4mTkhnV9lChoBmgJaA9DCGd/oNy2ozPAlIaUUpRoFUtKaBZHQIUq7NfPX051fZQoaAZoCWgPQwiBejNqvqRPwJSGlFKUaBVLTmgWR0CFKyIP9UCJdX2UKGgGaAloD0MIpdk8DoMkVcCUhpRSlGgVS2poFkdAhSuI/qxC6nV9lChoBmgJaA9DCIKPwYpT01XAlIaUUpRoFUtjaBZHQIUr8RQJokB1fZQoaAZoCWgPQwg+esN95HFawJSGlFKUaBVLdmgWR0CFLAJLM9r5dX2UKGgGaAloD0MItkdvuI+dWsCUhpRSlGgVS0RoFkdAhSw/Nqxkd3V9lChoBmgJaA9DCNcS8kHPNEjAlIaUUpRoFUtHaBZHQIUsV36hxo91fZQoaAZoCWgPQwi2gxH7BIhNwJSGlFKUaBVLQ2gWR0CFLF6Hj6vadX2UKGgGaAloD0MIPxwkRPmhYcCUhpRSlGgVS4RoFkdAhSyvMjeKsXV9lChoBmgJaA9DCG1vtyQHHl/AlIaUUpRoFUuAaBZHQIUsrxd6cAl1fZQoaAZoCWgPQwi7RsuBHhZXwJSGlFKUaBVLXWgWR0CFLOUjcEeRdX2UKGgGaAloD0MI7e9sj96CSsCUhpRSlGgVS1BoFkdAhSztvXK8tnV9lChoBmgJaA9DCCWuY1xxe2TAlIaUUpRoFUtdaBZHQIUtL212JSB1fZQoaAZoCWgPQwhAic+dYLNYwJSGlFKUaBVLdWgWR0CFLT+LFXJYdX2UKGgGaAloD0MIU8prJXR7WcCUhpRSlGgVS05oFkdAhS0+rMkhR3V9lChoBmgJaA9DCBdlNsgkblbAlIaUUpRoFUtuaBZHQIUtfXI2fkF1fZQoaAZoCWgPQwhD4bN1cMpOwJSGlFKUaBVLQmgWR0CFLdlYEGJOdX2UKGgGaAloD0MIbTmX4qrJWMCUhpRSlGgVS3ZoFkdAhS3pn6Eal3V9lChoBmgJaA9DCAFtq1lnQDzAlIaUUpRoFUteaBZHQIUuRz90ihZ1fZQoaAZoCWgPQwhuh4bFKBhmwJSGlFKUaBVLcmgWR0CFLnXJYDDCdX2UKGgGaAloD0MIF4OHad9JW8CUhpRSlGgVS0VoFkdAhS6pjDsMRnV9lChoBmgJaA9DCNkkP+JXEFHAlIaUUpRoFUtTaBZHQIUu0DuBtk51fZQoaAZoCWgPQwiIug9AaiBWwJSGlFKUaBVLWGgWR0CFLtm16Vt5dX2UKGgGaAloD0MIQtKnVfSqVMCUhpRSlGgVS0FoFkdAhS7PCVKPGXV9lChoBmgJaA9DCBUZHZCEz1jAlIaUUpRoFUtUaBZHQIUvIx+KCQN1fZQoaAZoCWgPQwj+YOC595BGwJSGlFKUaBVLS2gWR0CFLx/xUedTdX2UKGgGaAloD0MIr15FRgdgXMCUhpRSlGgVS2poFkdAhS926TW5H3V9lChoBmgJaA9DCAd96e3PJ03AlIaUUpRoFUt2aBZHQIUvgWLxZuB1fZQoaAZoCWgPQwh+HqM8811UwJSGlFKUaBVLTWgWR0CFL8bADaGpdX2UKGgGaAloD0MI6KT3ja91ScCUhpRSlGgVS0NoFkdAhS/uX/o7m3V9lChoBmgJaA9DCDB/hcyVWFfAlIaUUpRoFUtaaBZHQIUv5BAv+Ox1fZQoaAZoCWgPQwhiodY07x1ZwJSGlFKUaBVLZmgWR0CFMC0ALiMpdX2UKGgGaAloD0MISbn7HB+bUMCUhpRSlGgVS0VoFkdAhTCEK/mDDnV9lChoBmgJaA9DCCjv42iOkVTAlIaUUpRoFUtQaBZHQIUwqCUX5311fZQoaAZoCWgPQwis4/ih0hVTwJSGlFKUaBVLSGgWR0CFMMuM+/xldX2UKGgGaAloD0MIpYXLKmz5VsCUhpRSlGgVS35oFkdAhTDznq3VkXV9lChoBmgJaA9DCNDtJY3RClTAlIaUUpRoFUtLaBZHQIUxBz3h4t91ZS4="}, "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, "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 sha256:5453955deca3211ee74109dc9daecd40205f312a86975b38ff9341e48468593f
+size 147017

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 0x7fa0b2ea7b90>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa0b2ea7c20>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa0b2ea7cb0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa0b2ea7d40>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fa0b2ea7dd0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fa0b2ea7e60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa0b2ea7ef0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fa0b2ea7f80>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa0b2e2e050>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa0b2e2e0e0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa0b2e2e170>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fa0b2e6dbd0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        "n": 4,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 114688,
+    "_total_timesteps": 100000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1660291219.4428518,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQCUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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:": "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"
+    },
+    "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:df4c7803ab144f46f15c0544e9b3cf400a8c48f51c4d8d4b1de1f125362d282f
+size 87865

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:99625ab1da8200c299554b3b977f857288d8f33b3e8f9e3e0eb82c2795d518e4
+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": -17.387730206024013, "std_reward": 121.32696479815614, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-12T08:08:25.329198"}