Upload model

.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: 263.18 +/- 15.63
+      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 0x7e97244bccc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e97244bcd60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e97244bce00>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e97244bcea0>", "_build": "<function ActorCriticPolicy._build at 0x7e97244bcf40>", "forward": "<function ActorCriticPolicy.forward at 0x7e97244bcfe0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e97244bd080>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e97244bd120>", "_predict": "<function ActorCriticPolicy._predict at 0x7e97244bd1c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e97244bd260>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e97244bd300>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e97244bd3a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e972440e3c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1783513983184554186, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_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": 310, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 32, "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-6.6.122+-x86_64-with-glibc2.35 # 1 SMP Thu Apr 30 18:17:14 UTC 2026", "Python": "3.12.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.11.0+cu128", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.2", "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 sha256:5854c4a914662348d62b6f19e937b8ed1547833fc0ef44c232571a65a89a4315
+size 149054

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 0x7e97244bccc0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e97244bcd60>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e97244bce00>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e97244bcea0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7e97244bcf40>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7e97244bcfe0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e97244bd080>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e97244bd120>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7e97244bd1c0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e97244bd260>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e97244bd300>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e97244bd3a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7e972440e3c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1783513983184554186,
+    "learning_rate": 0.001,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAACAa6A9UhDKuZTvHbIFO4qxEVhGuyU++TIAAIA/AACAP02pEL2u54a6U8tXvbt3J7N3exE7Y+VMMwAAgD8AAIA/TXp1PYO0hj92qjE+MJFBvyDEQj2YsyY9AAAAAAAAAABmuCM99gxpulq87riHVVu0yXlPO0X7CTgAAIA/AACAP7NSrj4FZ0I/Qr5hvkPf5b4Yvdc9SJYcvgAAAAAAAAAAAOLevCm8HTn+xgA9d41DPez3gbvtsbE6AACAPwAAgD8NGao9rumEuvIVIDsmnZEy2QOiuWhl/TMAAIA/AACAPwBbxL1R6Zw/5ZTpvnUwKr9EFA++s9ZPvgAAAAAAAAAARuURPpSs1j5yjAO87WPxviDbJj22e1q9AAAAAAAAAAD6hUQ+3JnrPsXmZ74/gwK/lIWpvOaBDr4AAAAAAAAAAIBk8L0UzLg+NC+OPuUABr//r308ARYYPgAAAAAAAAAAc5T6vRhUrz92cCe/xIakvuxrur2QRrK+AAAAAAAAAAAabjO+k1N0P6ovTb5KVCG/WM1vvo2zdD0AAAAAAAAAAM2KPL3X2kO76RkLPXSjFj2YE9s8oPn7vQAAgD8AAIA/M2/pPETWEj645l2+yjHEvk7hnb0idbq9AAAAAAAAAAAAD+k9i2+qPoooSb5R+Aa/Y30hPM73Cb4AAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////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": 310,
+    "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": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 32,
+    "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 sha256:2eef91b3724315a2715ebe6ca8880a2ebe7087b92b97a1588f1c90936c392f87
+size 88695

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4acc6f021dceab1db9a0fb38191a20cf9294a63923dc3a2d052e4538f050d868
+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-6.6.122+-x86_64-with-glibc2.35 # 1 SMP Thu Apr 30 18:17:14 UTC 2026
+- Python: 3.12.13
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.11.0+cu128
+- GPU Enabled: True
+- Numpy: 2.0.2
+- Cloudpickle: 3.1.2
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:17cf3af4299a418cb11658c1fb7c9c402db3fc0cf47bde00d7f94d5c57c51344
+size 154270

results.json

@@ -0,0 +1 @@
+{"mean_reward": 263.1777269, "std_reward": 15.631830451701047, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2026-07-08T13:27:05.571878"}