PPO model for lunarlander environment

.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: 251.78 +/- 19.96
+      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 0x7bb17c504040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bb17c5040e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bb17c504180>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bb17c504220>", "_build": "<function ActorCriticPolicy._build at 0x7bb17c5042c0>", "forward": "<function ActorCriticPolicy.forward at 0x7bb17c504360>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bb17c504400>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bb17c5044a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7bb17c504540>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bb17c5045e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bb17c504680>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bb17c504720>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bb17cfa13c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1749402611901367794, "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "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:ec6d9f9a69834fc700d49b57f767b98105fe5edeb1f2f14eb141fd6c3a418c53
+size 148132

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 0x7bb17c504040>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bb17c5040e0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bb17c504180>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bb17c504220>",
+        "_build": "<function ActorCriticPolicy._build at 0x7bb17c5042c0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7bb17c504360>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bb17c504400>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bb17c5044a0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7bb17c504540>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bb17c5045e0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bb17c504680>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bb17c504720>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7bb17cfa13c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1749402611901367794,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAAATCwM+UmNMPlOhbL7/c4u+VKTfu5ogRr0AAAAAAAAAAGbmyDniVC4/WJ97PdANrr6pLR+7+BjqvAAAAAAAAAAAZr4iva6BrboC4tK7Gj2rNV18vjj5qxe1AACAPwAAgD8zD7a9vOC8P2bDCb88LWU7ZZDLvYOlpb4AAAAAAAAAABosZz4sopE/kv4WP7VbcL6SITQ+JFIVPgAAAAAAAAAApj6AvcMZZLopjbs6UX+MNQhPfrqmcNy5AACAPwAAgD+N4Ly9SOGNuopfJzRz+igwmSkiuyKpnbMAAIA/AACAP8aWKL6PpxS83cx3uvDsTLhOlH49Z8WaOQAAgD8AAIA/TTRJvcM9KLqoQLy6a9JOtmDkGbsMQL81AACAPwAAgD+a+5E84YiPurhIULwnENs2JlBUucapQ7YAAIA/AACAPzPzRbzsRKi7lucsu8KBmjwYMQs9GtOCvQAAgD8AAIA/AKAyPZmIiz+jsxw9cQe8vp5rLzy4LkM8AAAAAAAAAAAzT0m89uRduj5oabtcr422B5J4OEKViDoAAIA/AACAPzNfULwpCHK6o8kqOk17MTSydoK4rglIuQAAgD8AAIA/AJPivOFYlbqS9hI6QRLfNSyPJzlrZyi5AACAPwAAgD+m8Yk9KfBuusc/NLyf5zMzoapjOvOXSLMAAIA/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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08895519d92bcb173aa0dcc061682f7d96e96baf58306b2827065b28a61f04d8
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07e428040bba7c73d6a57e5c80bb514240046b94980e10e7ae0de3287dbf3f68
+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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
+- Python: 3.11.13
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.6.0+cu124
+- 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 sha256:5c0a35ac1053f295e1a1aa3789c24f77c1853309f0c39bb1ab4cca8666b68357
+size 158843

results.json

@@ -0,0 +1 @@
+{"mean_reward": 251.78434320000002, "std_reward": 19.958410349003753, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-06-08T17:36:26.252430"}