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: 259.22 +/- 23.46
+      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 0x7e79c588e7a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e79c588e840>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e79c588e8e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e79c588e980>", "_build": "<function ActorCriticPolicy._build at 0x7e79c588ea20>", "forward": "<function ActorCriticPolicy.forward at 0x7e79c588eac0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e79c588eb60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e79c588ec00>", "_predict": "<function ActorCriticPolicy._predict at 0x7e79c588eca0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e79c588ed40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e79c588ede0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e79c588ee80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e79c582f640>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1747116510123997061, "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "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": "3.11.12", "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:c7ac33cf5cc92ff9f2e7c391d52c4142f5fbc441d0386f9e0825a76251aa3402
+size 148120

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 0x7e79c588e7a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e79c588e840>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e79c588e8e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e79c588e980>",
+        "_build": "<function ActorCriticPolicy._build at 0x7e79c588ea20>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7e79c588eac0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e79c588eb60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e79c588ec00>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7e79c588eca0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e79c588ed40>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e79c588ede0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e79c588ee80>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7e79c582f640>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1747116510123997061,
+    "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:": "gAWVOgwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQDyLWkJrtVuMAWyUTQIBjAF0lEdAky0yydFvynV9lChoBkdAY4vwAlv602gHTegDaAhHQJMvKcz67/Z1fZQoaAZHQGYJDR2KVIJoB03oA2gIR0CTMtl0YCQtdX2UKGgGR0BuCSRdQfp2aAdNSgFoCEdAkzTqCxu89XV9lChoBkdAYLg+9Jz1b2gHTegDaAhHQJM14IToMa11fZQoaAZHQGNzHCoCMgloB03oA2gIR0CTOxfOUt7KdX2UKGgGR0BehZi7TUiIaAdN6ANoCEdAkzvRRMvh63V9lChoBkdAXktxYJVsDWgHTegDaAhHQJM/uCFsYVJ1fZQoaAZHQE6VQvYe1a5oB0vyaAhHQJM//TmW+oN1fZQoaAZHQGE92S2Yv39oB03oA2gIR0CTQAu6ErXldX2UKGgGR0BjXfddmg8KaAdN6ANoCEdAk0IZlBhQWXV9lChoBkdAa7abe/Ho5mgHTWQCaAhHQJNDpAcDKYB1fZQoaAZHQGZm7nHNorZoB03oA2gIR0CTQ9O2RaHLdX2UKGgGR0A50H2ys0YTaAdLuGgIR0CTTHtOEdvLdX2UKGgGR0A5dByjpLVXaAdL+mgIR0CTTkTPjXFtdX2UKGgGR0BlHm5vtMPCaAdN6ANoCEdAk1aClabF0nV9lChoBkdAYsnOM2m52GgHTegDaAhHQJNYKfh/Aj91fZQoaAZHQF2L4cWCVbBoB03oA2gIR0CTWEUPxx1gdX2UKGgGR0BftYy9EkSmaAdN6ANoCEdAk1yhPoFFD3V9lChoBkdAb/ZCdBjWkWgHTU4BaAhHQJN0V5Qgs9V1fZQoaAZHQGbK699MK1JoB03oA2gIR0CTdmX+2mYTdX2UKGgGR0Bi8iTyJ9ApaAdN6ANoCEdAk3febExZdXV9lChoBkdAcYGvHLida2gHTbYDaAhHQJN7AmzByjp1fZQoaAZHQG9bmHpKSPloB008AWgIR0CTfBJL/S6UdX2UKGgGR0BhkqzsyBTXaAdN6ANoCEdAk3x32RJVbXV9lChoBkdAcC4b9qDbrWgHTUwDaAhHQJN+aXjU/fR1fZQoaAZHQG4bYptrKvFoB02bAWgIR0CTfvOnEVFhdX2UKGgGR0Bn7Nzjm0VraAdN6ANoCEdAk4FKcEvCdnV9lChoBkdAZaIlWwNb1WgHTegDaAhHQJOB0mY0EYB1fZQoaAZHQGd3CHZbpvBoB03oA2gIR0CThSu76Hj7dX2UKGgGR0Blzd6gM+eOaAdN6ANoCEdAk4U3UQTVUnV9lChoBkdAbqrnoxHoYGgHTVwCaAhHQJOIjNTtLL91fZQoaAZHQGMQLg4wRGtoB03oA2gIR0CTiLqQzUI+dX2UKGgGR0BFmzy8SPELaAdL4GgIR0CTkcmPYFq0dX2UKGgGR0BxM7xWkrPMaAdNMAJoCEdAk5I8M/hVEXV9lChoBkdAcI2yn1nM+2gHTWMCaAhHQJOSzeLvTgF1fZQoaAZHQGVu3Qtz0YloB03oA2gIR0CTlBOdGy5adX2UKGgGR0Bu1VbkfcN6aAdN3QJoCEdAk5TFBhQWN3V9lChoBkdAcfinUDuBtmgHTSgCaAhHQJOWqBPKuCB1fZQoaAZHQHIsFkxyn1poB01aAmgIR0CTmj+FUQ05dX2UKGgGR0BwImRaHKwIaAdNOwFoCEdAk5qYUFjd6HV9lChoBkdAbuRItDlYEGgHTWICaAhHQJOdRrM1TBJ1fZQoaAZHQHA1p08vEjxoB03KAWgIR0CToeFzdUKidX2UKGgGR0ByIHLeQ+2WaAdNOwFoCEdAk7mG/nGKh3V9lChoBkdAcapQp4KQaWgHTRUDaAhHQJO+qlZX+2p1fZQoaAZHQGPStDUmUnpoB03oA2gIR0CTvtn+hoM8dX2UKGgGR0BxImy8jAzpaAdNBQJoCEdAk8IU7OmixnV9lChoBkdAbpfDWsijcmgHTWMBaAhHQJPCzronrpt1fZQoaAZHQHCbAmmce8xoB037AmgIR0CTw+FM7EHddX2UKGgGR0BwVLlU6xPgaAdNzANoCEdAk8QUB0ZFX3V9lChoBkdAbVqhbGFSKmgHTRkCaAhHQJPFgxM36yl1fZQoaAZHQGZyrWiDdxhoB03oA2gIR0CTx+z+FUQ1dX2UKGgGR0ByNxvKlpGnaAdNSwJoCEdAk8ho1UEPlXV9lChoBkdAcJREnLJSzmgHTYsCaAhHQJPJKlUIcBF1fZQoaAZHQG2y4jKPn0VoB02DAmgIR0CTySvvSc9XdX2UKGgGR0BvY8+1SflIaAdNEwJoCEdAk8qDbah6B3V9lChoBkdAaEFIaLn9vWgHTegDaAhHQJPKnOkcjqx1fZQoaAZHQEVb3mmtQsRoB0v1aAhHQJPNJXdTHbR1fZQoaAZHQHBbunAIpphoB03ZAWgIR0CT2WwVTJhfdX2UKGgGR0BqN7ch1TzeaAdN1wFoCEdAk94yT+vQnnV9lChoBkdAcB9Rh+fAbmgHTeoBaAhHQJPf2T5ftyB1fZQoaAZHQHET0kv9LpRoB03jAmgIR0CT4MBRAKOUdX2UKGgGR0BjnuWGATZhaAdN6ANoCEdAk+Tgl4TsY3V9lChoBkdAX99VDKHO8mgHTegDaAhHQJPpGP0Zm7J1fZQoaAZHQHFOwb6xgRdoB03NAmgIR0CT7C6qKgqWdX2UKGgGR0BvYD2L5ylvaAdN4AJoCEdAlALUYCQtBnV9lChoBkdAbWPu4wyqMmgHTU4BaAhHQJQEKjynUDx1fZQoaAZHQGXmpQ1rIo5oB03oA2gIR0CUBLbUwztUdX2UKGgGR0Bhw8qlP8AJaAdN6ANoCEdAlATO36Q/5nV9lChoBkdAcpiFB6a9b2gHTcgDaAhHQJQGOKxcE/11fZQoaAZHQGbd8QyylepoB03oA2gIR0CUBpvYe1a4dX2UKGgGR0Bx76Nm16VuaAdNqgFoCEdAlAbnT/hl2HV9lChoBkdAb9mrWAf+0mgHTf0BaAhHQJQG8sFt8/l1fZQoaAZHQHFHR6nivPloB01dA2gIR0CUCA1pTMq0dX2UKGgGR0BZjDDfm9xqaAdN6ANoCEdAlAidECvHLnV9lChoBkdAaO7XKbKA8WgHTegDaAhHQJQLkfbKzRh1fZQoaAZHQEEqN7SiM5xoB0vKaAhHQJQMW0svqTt1fZQoaAZHQGKwcqWkaddoB03oA2gIR0CUELbGFSKndX2UKGgGR0BxSK75Ec81aAdNaAFoCEdAlBNPD50r9XV9lChoBkdAb4yf29L6DWgHTVEBaAhHQJQUiCEpRXR1fZQoaAZHQHCsYVh1DBxoB01FAWgIR0CUFMfaYeDGdX2UKGgGR0Bw0BrhzeXSaAdNVgFoCEdAlBWLpzLfUHV9lChoBkdAcLRzhgmZ3WgHTYYBaAhHQJQVjONYKY11fZQoaAZHQD5zvw3HaOBoB0v9aAhHQJQXhzKcNH91fZQoaAZHQHKk6moBJZpoB01tAmgIR0CUGHe7tiQUdX2UKGgGR0ByGMpuuRs/aAdNSgNoCEdAlBrKy0KJEnV9lChoBkdAcYN95yEL6WgHTfsCaAhHQJQa16ol2Nh1fZQoaAZHQEAwOLiuMddoB0vOaAhHQJQcbIeYD1Z1fZQoaAZHQHFV1TrE9+xoB00BAmgIR0CUHJc+aBqcdX2UKGgGR0BwaVRm9QGfaAdNnwJoCEdAlB1sox59mnV9lChoBkdARXVxQzk6tGgHS+VoCEdAlCKr+T/yXnV9lChoBkdAcToQP7N0NmgHTecCaAhHQJQlSl54W1t1fZQoaAZHQHNbnmFJxvNoB01EAWgIR0CUJeyrPt2LdX2UKGgGR0BwzJ5X2dupaAdNtgFoCEdAlCbWeg+Ql3V9lChoBkdAcFdeCCjDbmgHTZwBaAhHQJQqUezUqhF1fZQoaAZHQHIfKI7/4qRoB01iAmgIR0CUKrTpPhybdX2UKGgGR0Bw/dG2CuloaAdN8AJoCEdAlCusiwB5o3V9lChoBkdAbXZZuhsZYWgHTXQBaAhHQJQt9rTH80l1fZQoaAZHQG+kl9a2WptoB02LAWgIR0CULv889wFUdX2UKGgGR0A6j5vcafjCaAdL1GgIR0CULz4oZydXdWUu"
+    },
+    "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 sha256:588e3f2e44dc8941f58c37d957dc23fc83a1f4b6846f504d408c3672e2834131
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46aa4eedf0b0fa09bad3438b1c11ee1b900680ae3d166beeb0dd3973c5e1d98a
+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: 3.11.12
+- 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:af9b16833abf264e01368d3eb0e37c2e8fd1d5a6b8ba06d7d087f6f8dc4a6936
+size 177224

results.json

@@ -0,0 +1 @@
+{"mean_reward": 259.2204260486443, "std_reward": 23.461711288779455, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-05-13T06:35:27.336163"}