Lunar Landar - v2 Stablebaseline3

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

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: 264.35 +/- 19.22
+      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 0x7e483d552de0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e483d552e80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e483d552f20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e483d552fc0>", "_build": "<function ActorCriticPolicy._build at 0x7e483d553060>", "forward": "<function ActorCriticPolicy.forward at 0x7e483d553100>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e483d5531a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e483d553240>", "_predict": "<function ActorCriticPolicy._predict at 0x7e483d5532e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e483d553380>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e483d553420>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e483d5534c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e483d6e01c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1759226161258500074, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAABmsuS8otoJPtiLUj279z2+4KakOx6QkT0AAAAAAAAAABNxGL7w4vs+DtosPcDPlr5w8x69vEk/PAAAAAAAAAAADSdxPii0qj6LnPq9nk5rvhkaND2X8B69AAAAAAAAAABaYGM+QZTTPbiHFL4ThoG+itl4ukf3pjwAAAAAAAAAAP1Rrz6MULM+uHqZvYFemb4mULg9XQp6PAAAAAAAAAAA2pQfvoUS8Ls7Ep04Yn5YNkK2Rz2BNMK3AACAPwAAgD9N3bE9NCS4PnYhFb3v0Yu+7HcFPXKpszoAAAAAAAAAAPiDj7747sY+atVHPgGcS75peA68+pLEPAAAAAAAAAAApm0APnPGGD/K77y9Kn2rvujHrjyacmG9AAAAAAAAAABNspA+4IN1P/r/OT5R882+fQpRPhWLvL0AAAAAAAAAAG0JBj7/G3A+UTaBvmxWdr7ABHi9GL6YPAAAAAAAAAAAc7hyPuZbDj+SI/E8Ze+VvnXO0j0ee4K9AAAAAAAAAAAznhm+BZjhu741KLu3IAS5PPBAPTbCWToAAIA/AACAP9pKsL0bXyA/kiCxvF/ap77X6Xu8BX5CvQAAAAAAAAAAAIoxvAV14T4+N8e95DSKvr8WAL3K/z+9AAAAAAAAAABzNSQ+nyKVPMo6i7ycwzi7T+QhPpemPLwAAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEEsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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": 620, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-6.6.97+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Sep  6 09:54:41 UTC 2025", "Python": "3.12.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.8.0+cu126", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "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 sha256:9b243c9ccb44557eefe75fb4483ecb73b8ca42058a9deeea7e5bd1fc4941b4f3
+size 149145

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 0x7e483d552de0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e483d552e80>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e483d552f20>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e483d552fc0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7e483d553060>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7e483d553100>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e483d5531a0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e483d553240>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7e483d5532e0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e483d553380>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e483d553420>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e483d5534c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7e483d6e01c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1759226161258500074,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAABmsuS8otoJPtiLUj279z2+4KakOx6QkT0AAAAAAAAAABNxGL7w4vs+DtosPcDPlr5w8x69vEk/PAAAAAAAAAAADSdxPii0qj6LnPq9nk5rvhkaND2X8B69AAAAAAAAAABaYGM+QZTTPbiHFL4ThoG+itl4ukf3pjwAAAAAAAAAAP1Rrz6MULM+uHqZvYFemb4mULg9XQp6PAAAAAAAAAAA2pQfvoUS8Ls7Ep04Yn5YNkK2Rz2BNMK3AACAPwAAgD9N3bE9NCS4PnYhFb3v0Yu+7HcFPXKpszoAAAAAAAAAAPiDj7747sY+atVHPgGcS75peA68+pLEPAAAAAAAAAAApm0APnPGGD/K77y9Kn2rvujHrjyacmG9AAAAAAAAAABNspA+4IN1P/r/OT5R882+fQpRPhWLvL0AAAAAAAAAAG0JBj7/G3A+UTaBvmxWdr7ABHi9GL6YPAAAAAAAAAAAc7hyPuZbDj+SI/E8Ze+VvnXO0j0ee4K9AAAAAAAAAAAznhm+BZjhu741KLu3IAS5PPBAPTbCWToAAIA/AACAP9pKsL0bXyA/kiCxvF/ap77X6Xu8BX5CvQAAAAAAAAAAAIoxvAV14T4+N8e95DSKvr8WAL3K/z+9AAAAAAAAAABzNSQ+nyKVPMo6i7ycwzi7T+QhPpemPLwAAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEEsIhpSMAUOUdJRSlC4="
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
+    },
+    "_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": 620,
+    "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "n_steps": 1024,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "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 sha256:598dfbb3aaafc9f9db3edc7cb1c5f8753e835a6c63a695f91b7245745eded7b2
+size 88695

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1c1b696825341ebccb8b1a45aa3ff186e259e6eccbc8a568f581a5bef633550b
+size 44095

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07c7431cf6005e7d8f367d79e995f63e2f9b981a37e3437b795d058f9af4308b
+size 1261

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.6.97+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Sep  6 09:54:41 UTC 2025
+- Python: 3.12.11
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.8.0+cu126
+- GPU Enabled: True
+- Numpy: 2.0.2
+- Cloudpickle: 3.1.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0990c1e7e4adcb7d7aae419ab3987df446f83c73d1e74e6b9654463152df67f3
+size 160000

results.json

@@ -0,0 +1 @@
+{"mean_reward": 264.3523136, "std_reward": 19.224744464212126, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-09-30T10:44:08.365440"}