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: 239.60 +/- 23.52
+      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 0x7f8e431b3e20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8e431b3eb0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8e431b3f40>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8e431c0040>", "_build": "<function ActorCriticPolicy._build at 0x7f8e431c00d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f8e431c0160>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8e431c01f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8e431c0280>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8e431c0310>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8e431c03a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8e431c0430>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8e431c04c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f8e43153440>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1714562365844607464, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9423ea12b3e1d872248b7447550737924ee066035a00f87f93fa14f30a31ddc6
+size 148088

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-LunarLander-v2/data

@@ -0,0 +1,99 @@
+{
+    "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 0x7f8e431b3e20>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8e431b3eb0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8e431b3f40>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8e431c0040>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f8e431c00d0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f8e431c0160>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f8e431c01f0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8e431c0280>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f8e431c0310>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8e431c03a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8e431c0430>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8e431c04c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f8e43153440>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1714562365844607464,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_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,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVRAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGS8JRGc4HaMAWyUTegDjAF0lEdAksZwrMC9y3V9lChoBkdAX9+zQeFL4GgHTegDaAhHQJLO+CGvfTF1fZQoaAZHQGBmWuxKQJZoB03oA2gIR0CS0fPZZjhDdX2UKGgGR0BghcEJSiudaAdN6ANoCEdAktzOf/WDpXV9lChoBkdAYVYOIZZSvWgHTegDaAhHQJLfPdEb5uZ1fZQoaAZHQGI9ZFgDzRRoB03oA2gIR0CS4JztkWhzdX2UKGgGR0BbCfepGWleaAdN6ANoCEdAkuHPGQ0XQHV9lChoBkdAYT1U4rBj4GgHTegDaAhHQJLuEqTbFjx1fZQoaAZHQGHKirDIikhoB03oA2gIR0CS7sLFn7HidX2UKGgGR0BiAP5FgDzRaAdN6ANoCEdAkvM04Nqgy3V9lChoBkdAX/GwX668QWgHTegDaAhHQJL0Y2qDK5l1fZQoaAZHQF72ZA6dUbVoB03oA2gIR0CTAdQWepXIdX2UKGgGR0BiapufmLccaAdN6ANoCEdAkwIU5ZKWcHV9lChoBkdAY98GGEf1YmgHTegDaAhHQJMEEQumJnB1fZQoaAZHQFzsRCx/ustoB03oA2gIR0CTBCTqB3A3dX2UKGgGR0BlDp+az/p/aAdN6ANoCEdAkyHQGr0aqHV9lChoBkdAVg7fcer+52gHTegDaAhHQJMpMBsANod1fZQoaAZHQFX+p/gBLf1oB03oA2gIR0CTMi0NjLB9dX2UKGgGR0Bh+cqx1PnCaAdN6ANoCEdAkzUhp1zQu3V9lChoBkdAYDkK4QSSNmgHTegDaAhHQJNANVbRne11fZQoaAZHQGAWcIzFdcBoB03oA2gIR0CTQjTtsvZidX2UKGgGR0BjXR3FDOTraAdN6ANoCEdAk0OVAmiQDHV9lChoBkdAWY1NxlxwQ2gHTegDaAhHQJNEoOOKfnR1fZQoaAZHQGKWXcYZVGVoB03oA2gIR0CTUASNwR5DdX2UKGgGR0Bjm9I3BHkMaAdN6ANoCEdAk1Cb9ycTanV9lChoBkdAWCrugHu7YmgHTegDaAhHQJNUt7RfF751fZQoaAZHQGIzHKnvUjNoB03oA2gIR0CTVeguRLbpdX2UKGgGR0BhJmYfGMn7aAdN6ANoCEdAk2MFzMibD3V9lChoBkdAYtvwqAjIJmgHTegDaAhHQJNjR1FH8TB1fZQoaAZHQFmOGOuJUHZoB03oA2gIR0CTZTkEcKgJdX2UKGgGR0BZ8vP5YYBOaAdN6ANoCEdAk2VM1KoQ4HV9lChoBkdAZP5CgsbvPWgHTegDaAhHQJODIOUdJat1fZQoaAZHQGHq95Qgs9VoB03oA2gIR0CTihj2zv7WdX2UKGgGR0BhVY2MsH0LaAdN6ANoCEdAk5H+Cf6Gg3V9lChoBkdAXsrRD1Gsm2gHTegDaAhHQJOUmctoSL91fZQoaAZHQGNGQazeGfxoB03oA2gIR0CTnbSElE7XdX2UKGgGR0BfNkNFz+3paAdN6ANoCEdAk6Ap4fOlf3V9lChoBkdAMvSDmKZUk2gHTXkBaAhHQJOgeSIP9UF1fZQoaAZHQFxOu6ErXlNoB03oA2gIR0CToV0YCQtBdX2UKGgGR0BlIOsq8UVSaAdN6ANoCEdAk6I58neBQXV9lChoBkdAYJLLGrCFbmgHTegDaAhHQJOrqLHdXT51fZQoaAZHQFfyJsfq5b1oB03oA2gIR0CTrCjo6jnFdX2UKGgGR0BhXcjPfKp2aAdN6ANoCEdAk6/GGh24eHV9lChoBkdAYhVqzqrzXmgHTegDaAhHQJOwuA3DNyJ1fZQoaAZHQCZBGvwEyL1oB01EAWgIR0CTtf71Iy0sdX2UKGgGR0BaN7WRRuTBaAdN6ANoCEdAk7xYi9qUNnV9lChoBkdAX9Ej1PFefWgHTegDaAhHQJO8j8yeqaR1fZQoaAZHQGBorrxAjY9oB03oA2gIR0CTvmLvCuU2dX2UKGgGR0Bk8GXPZ7HAaAdN6ANoCEdAk752RJVbRnV9lChoBkdAWjAug6EJ0GgHTegDaAhHQJPjJGwzLwF1fZQoaAZHQGHTlGG21D1oB03oA2gIR0CT69f5ULlWdX2UKGgGR0BhjjV6NVBEaAdN6ANoCEdAk+7JWNm16XV9lChoBkdAYmsNpdrwfGgHTegDaAhHQJP3L5ULlV91fZQoaAZHQGSyH/DLr5ZoB03oA2gIR0CT+aFcIJJHdX2UKGgGR0BixQXQ+lj3aAdN6ANoCEdAk/n4JRfnfXV9lChoBkdAY5PqsU7CBWgHTegDaAhHQJP7TAO8TSN1fZQoaAZHQGObuJLuhK1oB03oA2gIR0CUCGqpcX3ydX2UKGgGR0Bh9AyGi5/caAdN6ANoCEdAlAj1qveP73V9lChoBkdAY3h1ct5D7mgHTegDaAhHQJQMzv+fh/B1fZQoaAZHQGOz0g0TDfpoB03oA2gIR0CUDeJ9AooedX2UKGgGR0BeDzdLxqfwaAdN6ANoCEdAlBNmxyGSIXV9lChoBkdAXznytmtheGgHTegDaAhHQJQaCKNyYHB1fZQoaAZHQGW1U1AJLM9oB03oA2gIR0CUGjzTF2mpdX2UKGgGR0BkcBri2lVMaAdN6ANoCEdAlBwIcebNKXV9lChoBkdAYe0n3ta6jGgHTegDaAhHQJQcG6K+BYp1fZQoaAZHQF2DP/JeVs1oB03oA2gIR0CUQW7oSteVdX2UKGgGR0BmMbynUDuCaAdN6ANoCEdAlEqPZ7HAAXV9lChoBkdAZBrLWZqmCWgHTegDaAhHQJRNrF5v9+B1fZQoaAZHQGDaROclPadoB03oA2gIR0CUVqdhAnlXdX2UKGgGR0BkKx+H8CPqaAdN6ANoCEdAlFjJHqeK9HV9lChoBkdAYH+Ss8xKx2gHTegDaAhHQJRZCGUOd5J1fZQoaAZHQF+LIcBEKE5oB03oA2gIR0CUWoAFPi1idX2UKGgGR0BeorS7Xg+AaAdN6ANoCEdAlGjIAbQ1JnV9lChoBkdAWsEJ/oaDPGgHTegDaAhHQJRpU35vcah1fZQoaAZHQGLSKGlANXpoB03oA2gIR0CUbS1QqI8AdX2UKGgGR0Bkt9bu+h4/aAdN6ANoCEdAlG4/tMPBi3V9lChoBkdAX6U4dZJTVGgHTegDaAhHQJRzr41xbSt1fZQoaAZHQF0RHWBjFydoB03oA2gIR0CUekEXcgyNdX2UKGgGR0Bj20sJ6Y3OaAdN6ANoCEdAlHp5c9nscHV9lChoBkdAYn5uLJjlP2gHTegDaAhHQJR8Sy4Wk8B1fZQoaAZHQGTmuHWSU1RoB03oA2gIR0CUfFxMnJDFdX2UKGgGR0BmTtBUrCm/aAdN6ANoCEdAlJ+G07bL2nV9lChoBkdAMXxubZvkzWgHTT0BaAhHQJSiqqlxffJ1fZQoaAZHQFwwRXOnl4loB03oA2gIR0CUpxRhttQ9dX2UKGgGR0BiIFiQT238aAdN6ANoCEdAlKmXNLUTc3V9lChoBkdAY7a41gpjMGgHTegDaAhHQJSwgN7SiM51fZQoaAZHQFwauXeFcptoB03oA2gIR0CUshCMglnidX2UKGgGR0BhXtipeeFtaAdN6ANoCEdAlLI/5Lytm3V9lChoBkdAQqKTr3TNMWgHTRsBaAhHQJSybSofjjt1fZQoaAZHQGNbjkU9IPNoB03oA2gIR0CUswQSi/O/dX2UKGgGR0BjBHL9uP3jaAdN6ANoCEdAlL3phvze43V9lChoBkdAYWZXzUZvUGgHTegDaAhHQJS+kmzByjp1fZQoaAZHQF62xqfvnbJoB03oA2gIR0CUwzMb3oLYdX2UKGgGR0BDrX0wrUb2aAdNJQFoCEdAlMP7ZnL7oHV9lChoBkdAWOdp/PPcBWgHTegDaAhHQJTEJxHXmNl1fZQoaAZHQFnewDeTFERoB03oA2gIR0CUyQhqCYkWdX2UKGgGR0BlUrZpSJj2aAdN6ANoCEdAlM8DkELYw3V9lChoBkdAXnjl3hXKbWgHTegDaAhHQJTQuwcHWz51fZQoaAZHQGFtVkDp1RtoB03oA2gIR0CU0MvZRKpUdX2UKGgGR8Awbf8MuvlmaAdNOQFoCEdAlNca8UVSGnVlLg=="
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 248,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_shape": [
+            8
+        ],
+        "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "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,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:946ce7fce422d38ef57c7d1cb5a40bff457aea2e596cbc2aa00675c45068cb3d
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bee378c7bb0a2c6afa18d5dac350795fb3f0716bd842710780ede591d3022901
+size 43762

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.2.1+cu121
+- GPU Enabled: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 239.60265436247096, "std_reward": 23.515149950787123, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-01T11:50:40.479570"}