Upload PPO LunarLander-v2 trained agent

.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: 256.26 +/- 19.04
+      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 0x79c816c70fe0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79c816c71080>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79c816c71120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79c816c711c0>", "_build": "<function ActorCriticPolicy._build at 0x79c816c71260>", "forward": "<function ActorCriticPolicy.forward at 0x79c816c71300>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79c816c713a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79c816c71440>", "_predict": "<function ActorCriticPolicy._predict at 0x79c816c714e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79c816c71580>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79c816c71620>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79c816c716c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79c816dce780>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1771135278393254253, "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:": "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": 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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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-6.6.105+-x86_64-with-glibc2.35 # 1 SMP Thu Oct  2 10:42:05 UTC 2025", "Python": "3.12.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.9.0+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:e4463d63a2ba7af63af026ad2c9a28ca1b242af1984c178d3a831a2b76bbf06b
+size 149171

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 0x79c816c70fe0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79c816c71080>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79c816c71120>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79c816c711c0>",
+        "_build": "<function ActorCriticPolicy._build at 0x79c816c71260>",
+        "forward": "<function ActorCriticPolicy.forward at 0x79c816c71300>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x79c816c713a0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79c816c71440>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x79c816c714e0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79c816c71580>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79c816c71620>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x79c816c716c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x79c816dce780>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1771135278393254253,
+    "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:": "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": 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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
+        "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:ed55ca0c31e0b04d23bfa3e483783ba04f23bb7a9979b0ad1bd2442d59228680
+size 88695

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:43aafe52522d1027a18021220c337f99376fc3d6b7042066a1f60b866e517086
+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-6.6.105+-x86_64-with-glibc2.35 # 1 SMP Thu Oct  2 10:42:05 UTC 2025
+- Python: 3.12.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.9.0+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 sha256:00df0026247399f0d03dff70e9fc52be9f3d714492f1e6e9097a016d79ec1954
+size 163658

results.json

@@ -0,0 +1 @@
+{"mean_reward": 256.26337909999995, "std_reward": 19.043376513620693, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2026-02-15T06:49:41.519167"}