First version 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: 249.34 +/- 20.82
+      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 0x7f1dad3ebec0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1dad3ebf60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1dad3f0040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1dad3f00e0>", "_build": "<function ActorCriticPolicy._build at 0x7f1dad3f0180>", "forward": "<function ActorCriticPolicy.forward at 0x7f1dad3f0220>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1dad3f02c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1dad3f0360>", "_predict": "<function ActorCriticPolicy._predict at 0x7f1dad3f0400>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1dad3f04a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1dad3f0540>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1dad3f05e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f1dad30c140>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1749383831029156476, "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": 268, "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 sha256:59a3a405b553f5f53b69d1b299c8348a57d183796c0c2163eb404e4fde8e88e4
+size 148124

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 0x7f1dad3ebec0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1dad3ebf60>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1dad3f0040>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1dad3f00e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f1dad3f0180>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f1dad3f0220>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f1dad3f02c0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1dad3f0360>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f1dad3f0400>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1dad3f04a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1dad3f0540>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1dad3f05e0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f1dad30c140>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1749383831029156476,
+    "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:": "gAWVPAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHC7Dgdfb9KMAWyUTTABjAF0lEdAlkgQWBSUDHV9lChoBkdAcQZ1mapgkWgHTSIBaAhHQJZIPCgsbvR1fZQoaAZHQG7AxdyDIzZoB00sAWgIR0CWSZ39rGipdX2UKGgGR0BwzbGACnxbaAdNFQFoCEdAlknmk30f5nV9lChoBkdAbrrBGhEjPmgHTQ4BaAhHQJZKnsMRYih1fZQoaAZHQHDmKeoUBXFoB00UAWgIR0CWSsmdAgPmdX2UKGgGR0Byc/9VFQVLaAdNQAFoCEdAlkrdSIgvDnV9lChoBkdAcWOy5Zr57GgHTRUBaAhHQJZLnl3hXKd1fZQoaAZHQFFdzErGza9oB0vXaAhHQJZMt9KEnLJ1fZQoaAZHQHFpvpQk5ZNoB01eAWgIR0CWTUbgjyFxdX2UKGgGR0BwbFVWCEpRaAdNFwFoCEdAlk1wogFHKHV9lChoBkdAcCioCdSVGGgHTVkBaAhHQJZNxof0Vah1fZQoaAZHQHIKWTxG2CxoB00LAWgIR0CWTk7pV0cPdX2UKGgGR0Bu5CLuQZGbaAdNFgFoCEdAlk5sWO6un3V9lChoBkdASJRu2qkuYmgHS7hoCEdAlk/09dNWVHV9lChoBkdAcDOWtEG7jGgHTQwBaAhHQJZQQbaRISV1fZQoaAZHQG05SjQAuI1oB00xAWgIR0CWUH9ZRsMzdX2UKGgGR0Bmztd/rjYJaAdNcQJoCEdAllH57TlT33V9lChoBkdAcf9Mj/uLJmgHTRwBaAhHQJZSHCEYfnx1fZQoaAZHQHDYJHI6r/9oB00sAWgIR0CWUk4Wk8A8dX2UKGgGR0ByYMfozN2UaAdNZwFoCEdAllMCvkili3V9lChoBkdAcZ7gMtsen2gHTSwBaAhHQJZTMmlZX+51fZQoaAZHQHLWW0mdAgRoB000AWgIR0CWU6IHkcS5dX2UKGgGR0ByAtQYUFjeaAdNHQFoCEdAllO+yzHCGnV9lChoBkdARVKvaDf3vmgHTREBaAhHQJZU/hJiAlR1fZQoaAZHQG7pTYVZcLVoB003AWgIR0CWVY4gA6uGdX2UKGgGR0Bwnc8aGYa6aAdNNgFoCEdAllY8l5WzW3V9lChoBkdAcM88g6ltTGgHTTQBaAhHQJZWg7nxJ/Z1fZQoaAZHQHLZyAlOXVtoB01IAWgIR0CWV5hxo7FLdX2UKGgGR0BxXvMwDeTFaAdNRwFoCEdAllexMi8nNXV9lChoBkdAT5YFA3T/hmgHS8xoCEdAlle83Q2MsHV9lChoBkdAcV7Kxs2vS2gHTRkBaAhHQJZX9cqvvBt1fZQoaAZHQG7vgzguRLdoB00uAWgIR0CWWqqBVdX1dX2UKGgGR0BwDUHryDqXaAdNYgFoCEdAllrGLYPGyXV9lChoBkdAcvAKw6hg3WgHTRUBaAhHQJZbWbNKRMh1fZQoaAZHQHEs5GFzuF9oB01AAWgIR0CWW6aW5YozdX2UKGgGR0BxcyN1hb4baAdNKQFoCEdAllvG43FUAHV9lChoBkdASS2e8PFvRGgHS7doCEdAllvUahpQDXV9lChoBkdAbj5S9du50GgHTSMBaAhHQJZcZurIYFd1fZQoaAZHQHEsmattALRoB01IAWgIR0CWXWgAZKnOdX2UKGgGR0BQF1+7UXpGaAdLtGgIR0CWXZXK8tf5dX2UKGgGR0Bw1lbu+h4/aAdNKgFoCEdAll6O8CgbqHV9lChoBkdAcTL/nGKhtmgHTTMBaAhHQJZfzQdCE6F1fZQoaAZHQG9cqwpvxYtoB01vAWgIR0CWYAhaC+URdX2UKGgGR0BxFF9MK1G9aAdNFwFoCEdAlmBHWFvhqHV9lChoBkdAcadASFoL5WgHTW4BaAhHQJZi5xDLKV91fZQoaAZHQHDjHPmgam5oB01LAWgIR0CWeQosqaw2dX2UKGgGR0ByzG/KyOaOaAdNOAFoCEdAlnl2J3xFzHV9lChoBkdAcziZjhDPW2gHTUUBaAhHQJZ6XHT7VKB1fZQoaAZHQHB0gWWQfZFoB01XAWgIR0CWenrzGxUvdX2UKGgGR0Bv9G0Re1KHaAdNEwFoCEdAlnqyPIXCTHV9lChoBkdAcXIrX18LKGgHTRsBaAhHQJZ6w3sHB1t1fZQoaAZHQHDVk3CKrJdoB02AAWgIR0CWezF36hxpdX2UKGgGR0BvBG6wt8NQaAdNdwFoCEdAlnvuoxYaHnV9lChoBkdAcyIp5eJHiGgHS/xoCEdAlnyLQTmGNHV9lChoBkdAcaRvDxb0OGgHTTYBaAhHQJZ8zfNzKcN1fZQoaAZHQHCl4DxLCepoB002AWgIR0CWfgtPHktFdX2UKGgGR0BxHTdWQwK0aAdNYgFoCEdAln/i6tknTnV9lChoBkdAcEK336AOKGgHTR0BaAhHQJaASj7ALzB1fZQoaAZHQHGXw9A5aNdoB00NAWgIR0CWghKbKA8TdX2UKGgGR0BaFJiNKh+OaAdN6ANoCEdAloOIe5nUUnV9lChoBkdAcU5oyKvV3GgHTU0CaAhHQJaDqLHdXT51fZQoaAZHQHD0GYKIBR1oB00cAWgIR0CWg/+dsi0OdX2UKGgGR0BwQH58BuGcaAdNOQFoCEdAloQI1P3ztnV9lChoBkdAcYN+SKWLP2gHTS0BaAhHQJaEqSRr8BN1fZQoaAZHQHARM1baAWloB00LAWgIR0CWhMVFQVKxdX2UKGgGR0Bw7wSRKYiQaAdNQwFoCEdAloUbLpzLfXV9lChoBkdAbC8PBi1Aq2gHTS8BaAhHQJaGjBxgiNd1fZQoaAZHQG3TUE5hjONoB00mAWgIR0CWho0q6OHWdX2UKGgGR0ByaVW5paicaAdNagFoCEdAlob2IsRQJ3V9lChoBkdAcZcN83Mpw2gHTZkBaAhHQJaHk5q/M4d1fZQoaAZHQG/x2njyWiVoB00xAWgIR0CWh/cu8K5TdX2UKGgGR0Bt5+Lzf779aAdNIgFoCEdAlomO6I3zc3V9lChoBkdAchX8pCrtFGgHTVYBaAhHQJaKygf2bod1fZQoaAZHQEfHqBVdX1doB0v0aAhHQJaLT/DLr5Z1fZQoaAZHQFj9/Tb349JoB03oA2gIR0CWi4spobn6dX2UKGgGR0BwcYsyzollaAdNPwFoCEdAlowdVWCEpXV9lChoBkdAcGAyWAwwkGgHTSUBaAhHQJaMlrvb48F1fZQoaAZHQHJ/NBBzFMtoB00ZAWgIR0CWjTXj2i+MdX2UKGgGR0BvihTwUg0TaAdNPAFoCEdAlo08kleF+XV9lChoBkdAb5P/nW8RMGgHTTABaAhHQJaNRo24usd1fZQoaAZHQHGHBtP557hoB00nAWgIR0CWjX7wazeGdX2UKGgGR0BzNAH3UQTVaAdL/mgIR0CWjfKDTSb6dX2UKGgGR0BwkFM/QjUvaAdNCgFoCEdAlo5K6z3RHHV9lChoBkdAcH+xfv4M4WgHTTsBaAhHQJaOYhje9Bd1fZQoaAZHQG87YaP0Zm9oB000AWgIR0CWj47voePrdX2UKGgGR0BycKNDMNc4aAdNUAFoCEdAlpFR1gYxcnV9lChoBkdAbPLT/hl182gHTSUBaAhHQJaRwOYplSV1fZQoaAZHQHJeDxsl9jRoB02ZAWgIR0CWkyOFQEZBdX2UKGgGR0BvWQHJLdvbaAdNOQFoCEdAlpOyMLncL3V9lChoBkdAb32EEkjX4GgHTSUBaAhHQJaTzLGJemh1fZQoaAZHQG5IyPluFYdoB00nAWgIR0CWlHI9TxXodX2UKGgGR0ByLzH+6y0KaAdNUwFoCEdAlpUU3Ov+wXV9lChoBkdAbG6+8Gs3hmgHTQ0BaAhHQJaVFPdl/Yt1fZQoaAZHQHCSMlolD4RoB00aAWgIR0CWlTmALApKdX2UKGgGR0Bxky938n/laAdNHgFoCEdAlpVJDJEH+3V9lChoBkdAcV8h4+r2g2gHTScBaAhHQJaWWTJQtSR1fZQoaAZHQHB77qQiiZhoB00fAWgIR0CWln2h7E5ydX2UKGgGR0BwoI+9rXUZaAdNbQFoCEdAlpbx2W6bv3V9lChoBkdAcPZxKxs2vWgHTQkBaAhHQJaXXDCP6sR1ZS4="
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 268,
+    "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 sha256:33fb78bdf0c89bc5a7c29e858832ee9a604a9fcd7336ab37dd44f2d703fbebd4
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:72ea78d30869eaa8bb09bcfc7335dcca3aedc4d2bb6785b675cb736ccd8dbf21
+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:ccd2792e53a07b51832fd63fa8b8cd165a09142239a9e4893422143a33523e06
+size 150376

results.json

@@ -0,0 +1 @@
+{"mean_reward": 249.3411124, "std_reward": 20.815139498414858, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-06-08T12:25:31.152665"}