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: 267.49 +/- 21.18
+      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 0x783ed9964700>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x783ed9964790>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x783ed9964820>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x783ed99648b0>", "_build": "<function ActorCriticPolicy._build at 0x783ed9964940>", "forward": "<function ActorCriticPolicy.forward at 0x783ed99649d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x783ed9964a60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x783ed9964af0>", "_predict": "<function ActorCriticPolicy._predict at 0x783ed9964b80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x783ed9964c10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x783ed9964ca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x783ed9964d30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x783ed98ff800>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1707741021423895467, "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:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "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 sha256:19ae0953112cb557260a1988fc7fc17fcbbcac1d8e8633154811842eb3c3b901
+size 147992

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 0x783ed9964700>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x783ed9964790>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x783ed9964820>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x783ed99648b0>",
+        "_build": "<function ActorCriticPolicy._build at 0x783ed9964940>",
+        "forward": "<function ActorCriticPolicy.forward at 0x783ed99649d0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x783ed9964a60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x783ed9964af0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x783ed9964b80>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x783ed9964c10>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x783ed9964ca0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x783ed9964d30>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x783ed98ff800>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1707741021423895467,
+    "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:": "gAWVCgwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHE56B/ZuhuMAWyUS9GMAXSUR0CuVCD3VTaTdX2UKGgGR0BxdUGyHEdeaAdNEQFoCEdArlRYwudwvXV9lChoBkdAcao8JD3M6mgHTRwBaAhHQK5Umwi7kGR1fZQoaAZHQHEHEj1PFehoB0v6aAhHQK5UwnBtUGV1fZQoaAZHQHHNhgJC0F9oB00OAWgIR0CuVQbCSA6NdX2UKGgGR0BxzqzyBkI5aAdNCwFoCEdArlWvFo+OfnV9lChoBkdAcSVo8ZDRdGgHTRIBaAhHQK5VsjdHlOp1fZQoaAZHQHK4rG7z06JoB0voaAhHQK5V/NFjNIN1fZQoaAZHQHEfcZpBX0ZoB0v7aAhHQK5WANayKN11fZQoaAZHQHAZNPpIMBpoB0vPaAhHQK5WCPFvQ4V1fZQoaAZHQHL0+MuOCGxoB0v6aAhHQK5WL/Pw/gR1fZQoaAZHQG+mSU9pyp9oB0v7aAhHQK5Wc+qzZ6F1fZQoaAZHQG5wW6K+BYpoB00CAWgIR0CuVpdaMaS+dX2UKGgGR0ByB8baRISUaAdL42gIR0CuVq7nxJ/YdX2UKGgGR0Bwgte3QUpNaAdL4mgIR0CuVtXKr7wbdX2UKGgGR0Bs90piI+GHaAdL6mgIR0CuVughB7eEdX2UKGgGR0Bw+8nWrfcfaAdL/mgIR0CuVvZqdpZfdX2UKGgGR0Bx/TjQzDXOaAdNEwFoCEdArlfk45tFa3V9lChoBkdAcxHHymQ8wGgHS+1oCEdArlhDGJemenV9lChoBkdAcsWQ2uPmxWgHTRYBaAhHQK5YVdKujh11fZQoaAZHQHCL6x1PnCBoB00UAWgIR0CuWIpuuRs/dX2UKGgGR0BxU50HQhOhaAdL5GgIR0CuWRVjI7vHdX2UKGgGR0Bvbo8bJfY0aAdL1WgIR0CuWY2FFlTWdX2UKGgGR0BvgqWC2+fzaAdNBQFoCEdArlpCDyvs7nV9lChoBkdAc2Dm5lOGkGgHTRoBaAhHQK5axj7Q9id1fZQoaAZHQHKs3YL9deJoB0vnaAhHQK5a0YYR/Vl1fZQoaAZHQHK4Nnf2saNoB01AAWgIR0CuWvBx5s0pdX2UKGgGR0Bz9KCaqjrSaAdNBAFoCEdArlr5y2hIv3V9lChoBkdAcKkWvKU3XWgHS+1oCEdArlsRu0kWynV9lChoBkdAbmTSuyNXHWgHS+loCEdArlsYNRWLgnV9lChoBkdAc5/VoYekpWgHS+xoCEdArlsvOObRW3V9lChoBkdAc3Q4bCJoCmgHTT8BaAhHQK5bNPGhmGx1fZQoaAZHQHBuoUvf0mNoB01TAWgIR0CuXAopQUHqdX2UKGgGR0BwuR62OQyRaAdL+2gIR0CuXFtx+8XfdX2UKGgGR0BxzHMRpUPyaAdL+mgIR0CuXGTP0I1MdX2UKGgGR0BvRnrjYI0JaAdL8mgIR0CuXHBNM496dX2UKGgGR0Bw6OY5T6zmaAdNGAFoCEdArlx1gc94eXV9lChoBkdAcApY4ACGOGgHS/1oCEdArmVo5aNdaHV9lChoBkdAcePW0Z3s5WgHS+FoCEdArmXK13MY/HV9lChoBkdAc4TszEaVEGgHS9poCEdArmYCQkona3V9lChoBkdAcVVBd2PkrGgHS9doCEdArmYknmaH9HV9lChoBkdAc6il+Vkc0mgHTSkBaAhHQK5mTyAhB7h1fZQoaAZHQHC/YFJQLuxoB0v2aAhHQK5mfzjFQ2x1fZQoaAZHQHIiiI+GGmFoB0vnaAhHQK5mlyJbdJt1fZQoaAZHQG5+GSpzcRFoB00IAWgIR0CuZpwwCbMHdX2UKGgGR0BxZM+hXbM5aAdNBwFoCEdArmbUCLdepnV9lChoBkdAcyYQ8fV7QmgHTQ8BaAhHQK5nB56dDpl1fZQoaAZHQHKpkCV8kUtoB01JAWgIR0CuZ5lGoaUBdX2UKGgGR0BxO+lZX+2maAdL82gIR0CuZ9IWYWtVdX2UKGgGR0BybPMcIZ62aAdNEAFoCEdArmfosAeaKHV9lChoBkdAbtPAO8TSLWgHS/doCEdArmfn7m+0xHV9lChoBkdAciaVSGahH2gHTQYBaAhHQK5oH0aqCH11fZQoaAZHQHGTcIu5BkZoB0vfaAhHQK5ofmPo3aV1fZQoaAZHQHCHjRYzSCxoB0v/aAhHQK5oh1oQFs51fZQoaAZHQHGstMPBi1BoB0vUaAhHQK5or+uNgjR1fZQoaAZHQFVZG2TgVGloB0vKaAhHQK5pDw7T2Fp1fZQoaAZHQHCSMXSBshxoB0vcaAhHQK5pKliSaE11fZQoaAZHQHDgDnA6+39oB01xAWgIR0CuaYAaWHDadX2UKGgGR0BxOnrv9cbBaAdNJQFoCEdArmmdnwob43V9lChoBkdAcg+oQ4CIUWgHTSsBaAhHQK5p/tnf2sd1fZQoaAZHQHLYX4sVclhoB00bAWgIR0CuaqJyp71JdX2UKGgGR0ByhCYIBzV+aAdL+2gIR0Cuat+54GD+dX2UKGgGR0Bv934mCyyEaAdL72gIR0CuavIfCAMEdX2UKGgGR0Bt2TXJ5mh/aAdL8GgIR0Cuaw+e4Cp4dX2UKGgGR0BywEJlar3kaAdL+GgIR0Cua3IUJv5ydX2UKGgGR0BwYgRvm5lOaAdNewFoCEdArmt9XLeQ+3V9lChoBkdAcQaVQhwEQ2gHTWgBaAhHQK5rhvCMxXZ1fZQoaAZHQHKqEVWS2YxoB00SAWgIR0Cua404aP0adX2UKGgGR0BxvF35eqrBaAdL8mgIR0Cua/dqcmShdX2UKGgGR0BwmM9W6shgaAdNBwFoCEdArmwRd0JWvXV9lChoBkdAcC/aP0Zm7WgHS/toCEdArmxtVYISlHV9lChoBkdAcbc+4LCvYGgHS+5oCEdArmyuOS4e93V9lChoBkdAct8zND+irWgHS/ZoCEdArmztc6eXiXV9lChoBkdAbvOTdLxqf2gHTT8BaAhHQK5tgmLtNSJ1fZQoaAZHQHMdJW7voeRoB00NAWgIR0CubbSp71IzdX2UKGgGR0BzAPJW/8EWaAdL0WgIR0CubbjEvTPTdX2UKGgGR0Bw/hCiRGMGaAdL52gIR0Cubc1CgK4QdX2UKGgGR0ByJ4b+98JEaAdL0WgIR0CubeLHEMspdX2UKGgGR0Bwh4l1KXfJaAdNrQFoCEdArm5AxWT5f3V9lChoBkdAbrTeQ+2VmmgHS/FoCEdArm6hJAdGRXV9lChoBkdAcQYodMj/uWgHTR8BaAhHQK5u4PEKmbd1fZQoaAZHQHBCD/+85CFoB0v8aAhHQK5u6rZJ04l1fZQoaAZHQHLdX93r2QJoB0vVaAhHQK5u6tjCpFV1fZQoaAZHQG/+CfQKKHhoB0v4aAhHQK5u70Dlo111fZQoaAZHQHHhEMG5c1RoB00DAWgIR0CubxYZ/CqIdX2UKGgGR0BxYxgZ0jkdaAdLzWgIR0Cub2BlUZNxdX2UKGgGR0ByLwSxqwhXaAdL42gIR0Cub/+QdS2qdX2UKGgGR0BSqJRoAXEZaAdLuWgIR0CucDzkQwsYdX2UKGgGR0BvLSQV9F4LaAdNKgFoCEdArnBdKf4AS3V9lChoBkdAc9CqNIbwSmgHS+NoCEdArnE3seGO/HV9lChoBkdAbgdLTx5LRWgHS/VoCEdArnGXgrH2iHV9lChoBkdAcuAwHqu8smgHTTIBaAhHQK5xwyTINmV1fZQoaAZHQHGmGsvIwM9oB0vdaAhHQK5yAqU/wAl1fZQoaAZHQHBw2eg+QltoB00IAWgIR0CuciMHB1s+dX2UKGgGR0BTYw+EAYHgaAdLsmgIR0CucixN7BwddX2UKGgGR0BwyG8UVSGbaAdL4GgIR0CucqZl4C6pdX2UKGgGR0BxbbRSgoPTaAdNKgFoCEdArnKt9BrvcHV9lChoBkdAcGazD4xk/mgHS/5oCEdArnMIjv/ipHV9lChoBkdAcAWnTAnDzmgHTRIBaAhHQK5zJSw4bS91fZQoaAZHQG7T+DvmYBxoB00SAWgIR0Cuc1biZOSGdWUu"
+    },
+    "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "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 sha256:8772e22998bbebeed8b4b6c8fde99d55005e69e12da17c99379d3a98211709a2
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0fcb0aa4866dece2a45c10f878f90185b72896ec4505f9ce5adae8a85843617d
+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: 2.1.0+cu121
+- GPU Enabled: True
+- Numpy: 1.23.5
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 267.4887387999999, "std_reward": 21.181831374319913, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-12T12:58:02.533293"}