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: 242.93 +/- 16.51
+      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 0x7e53bc407ba0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e53bc407c40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e53bc407ce0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e53bc407d80>", "_build": "<function ActorCriticPolicy._build at 0x7e53bc407e20>", "forward": "<function ActorCriticPolicy.forward at 0x7e53bc407ec0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e53bc407f60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e53bc410040>", "_predict": "<function ActorCriticPolicy._predict at 0x7e53bc4100e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e53bc410180>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e53bc410220>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e53bc4102c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e53bc950380>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1756000474802800810, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAACa9tw8XOMlus7vP7tvc/w1agAtur1hXDoAAIA/AACAPxrkaL2m18E/dRSDvjqwwbzYep69D4oyvgAAAAAAAAAA5rUAPcNJQLr7zZo7hc/xteZJO7vOqOa0AACAPwAAgD/mp+s96GCNP0CLbz5mj7q+APD5PW7zqT0AAAAAAAAAAGaagz2PVk26JlLdO0keiDgo18I6ZulxuQAAgD8AAIA/ZiZ1vBRIm7p+Viw6lXqfNM1vybreXkW5AACAPwAAgD8A0jC8FLCZumktoDvnHYA4bjooNt5T87gAAIA/AACAP80FAL1cC2q6WlESus7QULZZxyM62/MrOQAAgD8AAIA/zRQRvUgbn7rK6YE6gAZxNexACDp4xJW5AACAPwAAgD8wNtI+9+fvPpsRTL7dU4++WmmWPZ2OP70AAAAAAAAAAE2r+j1Iody43nwyvE+qJ7rBPAg8kqUUuwAAgD8AAIA/AOLOPB8d8rm+pZO7osCeNbkXirp4NhK1AACAPwAAgD/KXIM+3YKLPzoeHz/bate+yvWxPkYzcT4AAAAAAAAAAOZYhT1I+YS6HsZ2usLUZrZVWjK7QvSPOQAAgD8AAIA/s1EhPXGNUrl+i0I6v8LlNXrFjDuSqNU0AACAPwAAgD9mCnA8j/p7ui4SrreaEqayndEOOwaZyzYAAIA/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": 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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 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:a8b6813e288c597b0d086156cbbd80455acbc6b12eac1c7a5880442db4ccea3f
+size 149195

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 0x7e53bc407ba0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e53bc407c40>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e53bc407ce0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e53bc407d80>",
+        "_build": "<function ActorCriticPolicy._build at 0x7e53bc407e20>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7e53bc407ec0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e53bc407f60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e53bc410040>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7e53bc4100e0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e53bc410180>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e53bc410220>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e53bc4102c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7e53bc950380>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1756000474802800810,
+    "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 sha256:84d7784fd78390ab0a4a8ec3cc4a9c7911efb36d9e9f248c26d40a09b28a6ffd
+size 88695

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:224bb97ea13704e9df3ab71c3c44c2322bbcf1899c63232e753a60d666ec74c2
+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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 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:ca6ac1bd7eb66781bb459a0e81940e2dbfd600f68d4041c96c6df883a25687cb
+size 165973

results.json

@@ -0,0 +1 @@
+{"mean_reward": 242.92780196526672, "std_reward": 16.514783347891118, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-08-24T02:18:57.627614"}