Upload PPO LunarLander-v2 trained agent - may10

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: 253.49 +/- 20.57
+      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 0x79cecb54dcf0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79cecb54dd80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79cecb54de10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79cecb54dea0>", "_build": "<function ActorCriticPolicy._build at 0x79cecb54df30>", "forward": "<function ActorCriticPolicy.forward at 0x79cecb54dfc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79cecb54e050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79cecb54e0e0>", "_predict": "<function ActorCriticPolicy._predict at 0x79cecb54e170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79cecb54e200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79cecb54e290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79cecb54e320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79cecb554980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1715327637957622803, "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:": "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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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"}, "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 sha256:0ce2a179bbcb53e013cd5ddbe622e6b4ef01c4e193bdb1727b44d05f1bd43ca8
+size 148072

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 0x79cecb54dcf0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79cecb54dd80>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79cecb54de10>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79cecb54dea0>",
+        "_build": "<function ActorCriticPolicy._build at 0x79cecb54df30>",
+        "forward": "<function ActorCriticPolicy.forward at 0x79cecb54dfc0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x79cecb54e050>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79cecb54e0e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x79cecb54e170>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79cecb54e200>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79cecb54e290>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x79cecb54e320>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x79cecb554980>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1715327637957622803,
+    "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:": "gAWVOQwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGVRvIn0CiiMAWyUTegDjAF0lEdAkYRai48U23V9lChoBkdAZdZwpe/pMmgHTegDaAhHQJGHzWSU1Q91fZQoaAZHQGfuBlUZNwloB03oA2gIR0CRjSwPRRdhdX2UKGgGR0BiiUEA5q/NaAdN6ANoCEdAkY3ZvkzXSXV9lChoBkdAL2At4A0bcWgHS8poCEdAkY9tNvfj0nV9lChoBkdAbMTO1OTJQ2gHTacCaAhHQJGTEt29tdl1fZQoaAZHQGSt+On2qT9oB03oA2gIR0CRmEKIznA7dX2UKGgGR0BkA9vybx3FaAdN6ANoCEdAkZvIh+vyLHV9lChoBkdAZO9qi48U22gHTegDaAhHQJGcWdH2AXl1fZQoaAZHQGYOT7/GVA1oB03oA2gIR0CRobvAGjbjdX2UKGgGR0BhWfv0AcT8aAdN6ANoCEdAkb2jbJwKjXV9lChoBkdAZH1y+6Ae72gHTegDaAhHQJHAq5/b0vp1fZQoaAZHQGHkOwX668RoB03oA2gIR0CRxJy1NQCTdX2UKGgGR0Bgl+h/RVp9aAdN6ANoCEdAkcsk6YE4enV9lChoBkdAZrHtzjm0V2gHTegDaAhHQJHNVOWSlnB1fZQoaAZHQGJbUA93bEhoB03oA2gIR0CRzY1ZTyavdX2UKGgGR0BdJMfq5byIaAdN6ANoCEdAkc9RczImxHV9lChoBkdAYmMcHWz4UWgHTegDaAhHQJHUEpsoDxN1fZQoaAZHQGSf+DnNgShoB03oA2gIR0CR2M48EFGHdX2UKGgGR0BEDmOuJUHZaAdL9mgIR0CR2UkmQbMpdX2UKGgGR0BgqTPjXFtLaAdN6ANoCEdAkdlg8B+4LHV9lChoBkdAZKKQtBfKIWgHTegDaAhHQJHavFjurp91fZQoaAZHQGLbyRSxZ+xoB03oA2gIR0CR3bXkHUtqdX2UKGgGR0BjyT3RG+bmaAdN6ANoCEdAkeLiONo8IXV9lChoBkdAOiLo8p1A7mgHS8ZoCEdAkeOjdxhlUnV9lChoBkdAS0dY2bXpW2gHS+poCEdAkeVPs3Q2M3V9lChoBkdARlwsRQJokGgHS9BoCEdAkeZA31jAi3V9lChoBkdAYvySIP9UCWgHTegDaAhHQJHm7wx33Yd1fZQoaAZHQGZBKABkqc5oB03oA2gIR0CR543ai9IxdX2UKGgGR0BetftlZowmaAdN6ANoCEdAke1gr1/UfHV9lChoBkdABq801qFh5WgHS9JoCEdAke+BsMy8BnV9lChoBkdAYZZPjXFtK2gHTegDaAhHQJIE3KfWcz91fZQoaAZHQGB4Qp4KQaJoB03oA2gIR0CSB3/YJ3PidX2UKGgGR0BhTnezlcQiaAdN6ANoCEdAkgtQBT4tYnV9lChoBkdAY7o1gpjMFGgHTegDaAhHQJISWJk5IYp1fZQoaAZHQGP6USAYpDxoB03oA2gIR0CSFRLrHEMtdX2UKGgGR0BoqLsrupjuaAdN6ANoCEdAkhfsgMc6vXV9lChoBkdAX0ZAZ88cMmgHTegDaAhHQJIfgVM23rl1fZQoaAZHQGO3j7IkqtpoB03oA2gIR0CSJp7ROUMYdX2UKGgGR0Bmt3QrtmcwaAdN6ANoCEdAkiwlXvH933V9lChoBkdAYnLDneSB9WgHTegDaAhHQJIyXSXt0FN1fZQoaAZHQGUmkhRqGlBoB03oA2gIR0CSM++JP69CdX2UKGgGR0BkAGalUIcBaAdN6ANoCEdAkjTK19fCynV9lChoBkdAXGmiDdxhlWgHTegDaAhHQJI1Uosqaw51fZQoaAZHQGIa8RlHz6JoB03oA2gIR0CSNdxagVXWdX2UKGgGR0BnUcGZ/kNnaAdN6ANoCEdAkjp+J+DvmnV9lChoBkdAZiSLyc0+DGgHTegDaAhHQJI8xyXD3uh1fZQoaAZHQGVh0QbuMMtoB03oA2gIR0CSVRMpPRAsdX2UKGgGR0Bka7+cYqG2aAdN6ANoCEdAklfnp0OmSHV9lChoBkdAOndg4Otnw2gHS99oCEdAklqFXzUZvXV9lChoBkdAYa5bO/tY0WgHTegDaAhHQJJbrDJlrdp1fZQoaAZHQGU9/GEPDpFoB03oA2gIR0CSYkLofSx8dX2UKGgGR0BlqJmqYJE6aAdN6ANoCEdAkmTskQf6oHV9lChoBkdAYOzjx0+1SmgHTegDaAhHQJJnCcSXdCV1fZQoaAZHQF7G9B8hLXdoB03oA2gIR0CSbLqX4TK1dX2UKGgGR0BklBuTA31jaAdN6ANoCEdAknMaXnhbW3V9lChoBkdAZ3ePuG9HtmgHTegDaAhHQJJ4xKzzErJ1fZQoaAZHQEN7VhCtzS1oB0vnaAhHQJJ6Z3pwCKd1fZQoaAZHQGZGuOCGvfVoB03oA2gIR0CSf5TQVsUJdX2UKGgGR0BlxyVB2OhkaAdN6ANoCEdAkoGUFOfukXV9lChoBkdAYhQuLaVUuWgHTegDaAhHQJKCrzPKMeh1fZQoaAZHQGYzFK9PDYRoB03oA2gIR0CSg2e/Yao/dX2UKGgGR0Bl2XGCI1tPaAdN6ANoCEdAkoQmvjfelHV9lChoBkdAZAkuvllsg2gHTegDaAhHQJKMyHKwIMV1fZQoaAZHQGNCKji4rjJoB03oA2gIR0CSolMeOn2qdX2UKGgGR0BhJ9Wn0kGBaAdN6ANoCEdAkqTgcYIjW3V9lChoBkdAZ35aJyhi9mgHTegDaAhHQJKnMQsf7rN1fZQoaAZHQGbIWw3YL9doB03oA2gIR0CSqDV7x/d7dX2UKGgGR0BkOWZgG8mKaAdN6ANoCEdAkq6IfKZDzHV9lChoBkdAYEUzk6tDD2gHTegDaAhHQJKw6O4oZyd1fZQoaAZHQGJDTeXRgJFoB03oA2gIR0CSsxlzltCRdX2UKGgGR0BgSVEd/8VIaAdN6ANoCEdAksGNz8xbjnV9lChoBkdAYc234sVclmgHTegDaAhHQJLG3tUn5SF1fZQoaAZHQGlPHa37UG5oB03oA2gIR0CSyFys0YTCdX2UKGgGR0BohIvDgqEwaAdN6ANoCEdAksxswDeTFHV9lChoBkdAZxF5C4SYgWgHTegDaAhHQJLNzMJQcgh1fZQoaAZHQGTjGZ/kNnZoB03oA2gIR0CSzo7ihnJ1dX2UKGgGR0BoMwaR6nivaAdN6ANoCEdAks8A9V3ljnV9lChoBkdAZyvRKHwgDGgHTegDaAhHQJLPb8uSOip1fZQoaAZHQGc1K0MPSUloB03oA2gIR0CS1eVUdaMadX2UKGgGR0BS/C9mHxjKaAdL02gIR0CS2ZDBuXNUdX2UKGgGR0Bho8cGTs6aaAdN6ANoCEdAktniMYMvy3V9lChoBkdAY4LgYxcmjWgHTegDaAhHQJLw4+A3DN11fZQoaAZHQGNUBVENOM5oB03oA2gIR0CS8+8b70nPdX2UKGgGR0Biz/bdrO7haAdN6ANoCEdAkvTr8Jlar3V9lChoBkdAYFZYzSCvo2gHTegDaAhHQJL6/kNnXd11fZQoaAZHQF9I3N9ph4NoB03oA2gIR0CS/XxFRYRvdX2UKGgGR0BjUZ00WM0haAdN6ANoCEdAkv983qAz6HV9lChoBkdASrZXhfjS5WgHS9BoCEdAkv/3JYDDCXV9lChoBkdAMtfdhy8zymgHS+hoCEdAkwf42bXpW3V9lChoBkdAZ460iQkonmgHTegDaAhHQJMLZJ2+wkh1fZQoaAZHQGJ6dZ7ojfNoB03oA2gIR0CTEP9roGILdX2UKGgGR0BjPauSwGGEaAdN6ANoCEdAkxKlR51Ng3V9lChoBkdAXauuZCv5g2gHTegDaAhHQJMXPIJZ4fR1fZQoaAZHQGZ/aciGFi9oB03oA2gIR0CTGL/0dzXCdX2UKGgGR0Bg135DZ13daAdN6ANoCEdAkxmTNhVlw3V9lChoBkdAYznnf2saKmgHTegDaAhHQJMaElKK5091fZQoaAZHQGM3ur6tT1loB03oA2gIR0CTJKgk1MufdX2UKGgGR0BbCi9mHxjKaAdN6ANoCEdAkynQMhHLBHV9lChoBkdAYQxBlcyFf2gHTegDaAhHQJMqLCHh0hh1ZS4="
+    },
+    "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:d5395558844b732fdde872ef96e8199d88cd1639b6669821eccae334db134fc0
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4c09809f512fcb90dcabc646d92be08c77d38f62ec124ba0c25867d3f12f619f
+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": 253.49231265203622, "std_reward": 20.57160219736931, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-10T08:19:38.329883"}