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: 252.87 +/- 20.63
+      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 0x7f17b2c4cdc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f17b2c4ce50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f17b2c4cee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f17b2c4cf70>", "_build": "<function ActorCriticPolicy._build at 0x7f17b2bd0040>", "forward": "<function ActorCriticPolicy.forward at 0x7f17b2bd00d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f17b2bd0160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f17b2bd01f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f17b2bd0280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f17b2bd0310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f17b2bd03a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f17b2bd0430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f17b2c4b3c0>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676540042526176185, "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:": "gAWVgRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIUfTAx+BSZUCUhpRSlIwBbJRN6AOMAXSUR0CSTIH6MzdldX2UKGgGaAloD0MIcxHfiVnLYkCUhpRSlGgVTegDaBZHQJJPH779AHF1fZQoaAZoCWgPQwhpVOBkG31bQJSGlFKUaBVN6ANoFkdAklTtFBppOHV9lChoBmgJaA9DCLGJzFxgqWRAlIaUUpRoFU3oA2gWR0CSVYkf9xZMdX2UKGgGaAloD0MIC/FIvLz8YUCUhpRSlGgVTegDaBZHQJJdjkNnXd11fZQoaAZoCWgPQwgQP/89+HZiQJSGlFKUaBVN6ANoFkdAkm17ORkmQnV9lChoBmgJaA9DCC6RC85gLmNAlIaUUpRoFU3oA2gWR0CScDouwosqdX2UKGgGaAloD0MIzSIUW0EVXUCUhpRSlGgVTegDaBZHQJJxPmGM4tJ1fZQoaAZoCWgPQwin5nKDIUVjQJSGlFKUaBVN6ANoFkdAknJn3L3bmHV9lChoBmgJaA9DCLPr3orEgWVAlIaUUpRoFU3oA2gWR0CSc0l6Z6UrdX2UKGgGaAloD0MIxFxStd01XUCUhpRSlGgVTegDaBZHQJJ7xI065oZ1fZQoaAZoCWgPQwhRFVPpJ8RiQJSGlFKUaBVN6ANoFkdAkoPm/Firk3V9lChoBmgJaA9DCO+oMSFmZmJAlIaUUpRoFU3oA2gWR0CShKxKxs2vdX2UKGgGaAloD0MIB3jSwuXnY0CUhpRSlGgVTegDaBZHQJKMEEgW8Ad1fZQoaAZoCWgPQwhnKVlOwkJgQJSGlFKUaBVN6ANoFkdAko0fnGKhtnV9lChoBmgJaA9DCBKgppYt22RAlIaUUpRoFU3oA2gWR0CSj82A5JbudX2UKGgGaAloD0MIWVAYlGnyZUCUhpRSlGgVTegDaBZHQJKtIhxHXmN1fZQoaAZoCWgPQwjymeyfJzplQJSGlFKUaBVN6ANoFkdAkq/awt8NQXV9lChoBmgJaA9DCH/cfvlkFV9AlIaUUpRoFU3oA2gWR0CStZs7+1jRdX2UKGgGaAloD0MIIenTKvouYECUhpRSlGgVTegDaBZHQJK2NiMHbAV1fZQoaAZoCWgPQwirsBnggq9cQJSGlFKUaBVN6ANoFkdAkrzKXKKYRnV9lChoBmgJaA9DCFN40Oy67WFAlIaUUpRoFU3oA2gWR0CSyAFGG21EdX2UKGgGaAloD0MIyol2FdLrYkCUhpRSlGgVTegDaBZHQJLK8Rsdkrh1fZQoaAZoCWgPQwg+lj50QV9iQJSGlFKUaBVN6ANoFkdAkswRakhzNnV9lChoBmgJaA9DCED7kSKy1mJAlIaUUpRoFU3oA2gWR0CSzdyp71IzdX2UKGgGaAloD0MIF/NzQ9NmZECUhpRSlGgVTegDaBZHQJLPMUO/cnF1fZQoaAZoCWgPQwga+ie4WC5cQJSGlFKUaBVN6ANoFkdAktwWQnx8UnV9lChoBmgJaA9DCCoAxjNoX2VAlIaUUpRoFU3oA2gWR0CS5Qw6QvHtdX2UKGgGaAloD0MIA7NCkW4fZECUhpRSlGgVTegDaBZHQJLl1KpT/AF1fZQoaAZoCWgPQwgzMshdBKphQJSGlFKUaBVN6ANoFkdAku1N12aDw3V9lChoBmgJaA9DCOEH51NHwGNAlIaUUpRoFU3oA2gWR0CS7lKuB+WodX2UKGgGaAloD0MIQpdw6C13ZUCUhpRSlGgVTegDaBZHQJLw+zhP0qZ1fZQoaAZoCWgPQwiuoGmJFVRmQJSGlFKUaBVN6ANoFkdAkwsM2zfJm3V9lChoBmgJaA9DCNqu0AdLqGNAlIaUUpRoFU3oA2gWR0CTDvJGe+VUdX2UKGgGaAloD0MIR450BsYeYECUhpRSlGgVTegDaBZHQJMXGPkq+al1fZQoaAZoCWgPQwhU5BBx80lkQJSGlFKUaBVN6ANoFkdAkxfFoYekpXV9lChoBmgJaA9DCJYKKqp+o2RAlIaUUpRoFU3oA2gWR0CTHkajesPrdX2UKGgGaAloD0MIBHEeTuAyY0CUhpRSlGgVTegDaBZHQJMp8k7fYSR1fZQoaAZoCWgPQwgQzTy5pvtbQJSGlFKUaBVN6ANoFkdAkyzB9LHuJHV9lChoBmgJaA9DCEMbgA0I12NAlIaUUpRoFU3oA2gWR0CTLc3OObRXdX2UKGgGaAloD0MISDMWTecgZUCUhpRSlGgVTegDaBZHQJMvBkSVW0Z1fZQoaAZoCWgPQwgB9zx/2s9fQJSGlFKUaBVN6ANoFkdAky/5ZGKAKHV9lChoBmgJaA9DCMfVyK601WFAlIaUUpRoFU3oA2gWR0CTOIvhZQpGdX2UKGgGaAloD0MIWCB6UqYZYkCUhpRSlGgVTegDaBZHQJNBAjFAE+x1fZQoaAZoCWgPQwij5xa6EoJfQJSGlFKUaBVN6ANoFkdAk0IG2TgVGnV9lChoBmgJaA9DCOQvLeqTsGRAlIaUUpRoFU3oA2gWR0CTTHhlDneSdX2UKGgGaAloD0MIllrvN9opY0CUhpRSlGgVTegDaBZHQJNOAbwSamZ1fZQoaAZoCWgPQwhTP28qUh5hQJSGlFKUaBVN6ANoFkdAk1FGZNO/L3V9lChoBmgJaA9DCAYsuYrFsGZAlIaUUpRoFU3oA2gWR0CTVk6eGwiadX2UKGgGaAloD0MIRS+jWO50Y0CUhpRSlGgVTegDaBZHQJNr/420iQl1fZQoaAZoCWgPQwjjcOZXc5JIQJSGlFKUaBVNMAFoFkdAk2yGACnxa3V9lChoBmgJaA9DCINNnUdFGmRAlIaUUpRoFU3oA2gWR0CTch/6wdKedX2UKGgGaAloD0MIcyuE1VgjYkCUhpRSlGgVTegDaBZHQJNyrLeQ+2V1fZQoaAZoCWgPQwhHkEqxo/xfQJSGlFKUaBVN6ANoFkdAk3j+mR/3FnV9lChoBmgJaA9DCASqfxBJ7mNAlIaUUpRoFU3oA2gWR0CTh4pYcNpedX2UKGgGaAloD0MIVaAWg4c2V0CUhpRSlGgVTegDaBZHQJOK3xAjY7J1fZQoaAZoCWgPQwh1AS8zbE9kQJSGlFKUaBVN6ANoFkdAk4vcWfseGXV9lChoBmgJaA9DCInPnWD/xl5AlIaUUpRoFU3oA2gWR0CTjRyo4uK5dX2UKGgGaAloD0MIJEVkWMVQZkCUhpRSlGgVTegDaBZHQJOOFAX2ugZ1fZQoaAZoCWgPQwip3a8CfOcwQJSGlFKUaBVNDAFoFkdAk49pI+W4VnV9lChoBmgJaA9DCNY2xeOismVAlIaUUpRoFU3oA2gWR0CTloM4cWCVdX2UKGgGaAloD0MIotEdxM5HYUCUhpRSlGgVTegDaBZHQJOfW7dznzR1fZQoaAZoCWgPQwhe1VktsHVkQJSGlFKUaBVN6ANoFkdAk6cs5Ke05XV9lChoBmgJaA9DCNEi2/n+kWNAlIaUUpRoFU3oA2gWR0CTqEXNke6qdX2UKGgGaAloD0MIEk4LXvT6X0CUhpRSlGgVTegDaBZHQJOrAY+B6KN1fZQoaAZoCWgPQwjBdFq3QWlmQJSGlFKUaBVN6ANoFkdAk7BEiY9gW3V9lChoBmgJaA9DCCmxa3u7OWJAlIaUUpRoFU3oA2gWR0CTs67cfvF4dX2UKGgGaAloD0MIkdRCyeTYXUCUhpRSlGgVTegDaBZHQJPLmn+AEuB1fZQoaAZoCWgPQwgKEXAIVY1kQJSGlFKUaBVN6ANoFkdAk9BZQLux8nV9lChoBmgJaA9DCMlaQ6m9Ul9AlIaUUpRoFU3oA2gWR0CT0OBBAv+PdX2UKGgGaAloD0MIYCFzZdC6ZUCUhpRSlGgVTegDaBZHQJPhu54GD+R1fZQoaAZoCWgPQwiqgeZz7tReQJSGlFKUaBVN6ANoFkdAk+Rn0Gu9vnV9lChoBmgJaA9DCOHvF7OlKGNAlIaUUpRoFU3oA2gWR0CT5YrWiDdydX2UKGgGaAloD0MIutv10hTGWUCUhpRSlGgVTegDaBZHQJPm0OI68xt1fZQoaAZoCWgPQwhg5GVNLHVkQJSGlFKUaBVN6ANoFkdAk+fGahHsknV9lChoBmgJaA9DCPynGyhw9GRAlIaUUpRoFU3oA2gWR0CT6TPAO8TSdX2UKGgGaAloD0MIq9BALJsUX0CUhpRSlGgVTegDaBZHQJPypSJj2Bd1fZQoaAZoCWgPQwilTkAT4bljQJSGlFKUaBVN6ANoFkdAk/36ujh1knV9lChoBmgJaA9DCNpTck7sc2ZAlIaUUpRoFU3oA2gWR0CUBiu89Oh1dX2UKGgGaAloD0MI3zZTIZ4pZ0CUhpRSlGgVTegDaBZHQJQHpzxPO6d1fZQoaAZoCWgPQwiny2Ji84ZiQJSGlFKUaBVN6ANoFkdAlAuJj+aScXV9lChoBmgJaA9DCOc24V4Z1GVAlIaUUpRoFU3oA2gWR0CUEycUdq+KdX2UKGgGaAloD0MI5nYv98k+ZECUhpRSlGgVTegDaBZHQJQWovf0mMR1fZQoaAZoCWgPQwj191J40LRfQJSGlFKUaBVN6ANoFkdAlBcXNgSey3V9lChoBmgJaA9DCKjIIeLmmmRAlIaUUpRoFU3oA2gWR0CUM8PMB6rvdX2UKGgGaAloD0MIwcWKGszlYUCUhpRSlGgVTegDaBZHQJQ0UzN2TxJ1fZQoaAZoCWgPQwj8yK1Jt0BgQJSGlFKUaBVN6ANoFkdAlEbE7bL2YnV9lChoBmgJaA9DCH8zMV0IXmNAlIaUUpRoFU3oA2gWR0CUSeE7W/ahdX2UKGgGaAloD0MIprVpbK/WXUCUhpRSlGgVTegDaBZHQJRLFzEJjUd1fZQoaAZoCWgPQwhVTRB1n+dmQJSGlFKUaBVN6ANoFkdAlExs3Q2MsHV9lChoBmgJaA9DCDNS76kcBmZAlIaUUpRoFU3oA2gWR0CUTXj+aScLdX2UKGgGaAloD0MIz0iERrBwZUCUhpRSlGgVTegDaBZHQJRO+glF+d91fZQoaAZoCWgPQwjJAFDFDVhhQJSGlFKUaBVN6ANoFkdAlFZifg75mHV9lChoBmgJaA9DCL/VOnE5ymFAlIaUUpRoFU3oA2gWR0CUYH4dIXj3dX2UKGgGaAloD0MIvFtZojNfY0CUhpRSlGgVTegDaBZHQJRrAIppeu51fZQoaAZoCWgPQwi/YDdsW5hdQJSGlFKUaBVN6ANoFkdAlGx0XtShrXV9lChoBmgJaA9DCMu8VdchYmNAlIaUUpRoFU3oA2gWR0CUb12tuDSPdX2UKGgGaAloD0MIrdug9lu5YECUhpRSlGgVTegDaBZHQJR0du1ndwh1fZQoaAZoCWgPQwhLV7CN+NJhQJSGlFKUaBVN6ANoFkdAlHcC+tbLU3V9lChoBmgJaA9DCOdtbHak511AlIaUUpRoFU3oA2gWR0CUd2k7wKBvdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:776be4277cee4ff982b1f4a7667fb92d79671a3f4939466f4e6090c472ae4244
+size 147424

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 0x7f17b2c4cdc0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f17b2c4ce50>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f17b2c4cee0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f17b2c4cf70>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f17b2bd0040>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f17b2bd00d0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f17b2bd0160>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f17b2bd01f0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f17b2bd0280>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f17b2bd0310>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f17b2bd03a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f17b2bd0430>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f17b2c4b3c0>"
+    },
+    "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": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1676540042526176185,
+    "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": 248,
+    "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 sha256:4a2d2f05252a164d74a07b31628ee2bfaa71d51e3bc312466bba35fa95dfa685
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:919820e3b9cb70410cf2161b9d948d6370bf1801b6ea921dcfae05b2d5e836df
+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: 1.21.6
+- Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 252.87240081490444, "std_reward": 20.629409968737946, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-16T10:03:40.783287"}