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

@@ -1,3 +1,37 @@
----
-license: mit
----
+---
+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: 243.08 +/- 19.82
+      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 0x7aa6ec505080>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7aa6ec505120>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7aa6ec5051c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7aa6ec505260>", "_build": "<function ActorCriticPolicy._build at 0x7aa6ec505300>", "forward": "<function ActorCriticPolicy.forward at 0x7aa6ec5053a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7aa6ec505440>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7aa6ec5054e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7aa6ec505580>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7aa6ec505620>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7aa6ec5056c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7aa6ec505760>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7aa6ec664200>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1740382909223304330, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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:": "gAWVQwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGB0HP3SKFaMAWyUTegDjAF0lEdAkpWBYV6/qXV9lChoBkdAXgQtUXHim2gHTegDaAhHQJKW0VFhG6R1fZQoaAZHQGMo+Hi3ocJoB03oA2gIR0CSn9AfMfRvdX2UKGgGR0BixFsnAqNIaAdN6ANoCEdAkqK7SVnmJXV9lChoBkdAZHOL1EmY0GgHTegDaAhHQJKjQmsvIwN1fZQoaAZHQGGXopx3mmtoB03oA2gIR0CSqY+wkgOjdX2UKGgGR0BhqF6LOzIFaAdN6ANoCEdAkquy9M9KVnV9lChoBkdAW86q6vq1PWgHTegDaAhHQJKsTH1e0HB1fZQoaAZHQGVQFp48loloB03oA2gIR0CSs354GD+SdX2UKGgGR0BsDqup0fYBaAdN8gFoCEdAkrUnXZoPCnV9lChoBkdAYlitcOby6WgHTegDaAhHQJLME2Q4jr11fZQoaAZHQGG2hHbypaRoB03oA2gIR0CSz9OzIFNddX2UKGgGR0BkbuSSvC/HaAdN6ANoCEdAktIMurZJ1HV9lChoBkdAXTK9qUNayWgHTegDaAhHQJLTjp8neBR1fZQoaAZHQGPj8QZn+Q5oB03oA2gIR0CS4w1dgOSXdX2UKGgGR0BkGu8f3evZaAdN6ANoCEdAkuQTTjNpunV9lChoBkdAY53ycTakAWgHTegDaAhHQJLls0Ltu1p1fZQoaAZHQGRpUNrj5sVoB03oA2gIR0CS6JTuv2XcdX2UKGgGR0BgRgc1fmcOaAdN6ANoCEdAkvY6P0Zm7XV9lChoBkdAYb21O0svqWgHTegDaAhHQJL5NtbcGkh1fZQoaAZHQGUH2KEWZZ1oB03oA2gIR0CS+cfpljEvdX2UKGgGR0BfkREv0yxiaAdN6ANoCEdAkwCYYFaB7XV9lChoBkdAZsJvfj0cwWgHTegDaAhHQJMEX0TURWd1fZQoaAZHQGCzWGATZg5oB03oA2gIR0CTBT0HyEtedX2UKGgGR0BgcVj3Ehq1aAdN6ANoCEdAkxBJLVWjoXV9lChoBkdAYkBD+BH09WgHTegDaAhHQJMScqbz9TB1fZQoaAZHQG1Av1DjR2NoB02gAWgIR0CTGLCW/rSmdX2UKGgGR0BozVyq+8GtaAdNpgNoCEdAkxkIWk8A73V9lChoBkdAZacEGJN0vGgHTegDaAhHQJMZkbCJoCd1fZQoaAZHQCwN7ngYP5JoB00uAWgIR0CTLIIInjQzdX2UKGgGR0BsjQrUb1h9aAdNeQJoCEdAky0/gvUSZnV9lChoBkdAYdZbXYlIE2gHTegDaAhHQJMxGK2rn1Z1fZQoaAZHQGKUEKE384xoB03oA2gIR0CTMqtW+49YdX2UKGgGR0BwDUZYPoV3aAdNqgNoCEdAkz1v8VHnU3V9lChoBkdAYVhxDLKV6mgHTegDaAhHQJNCSy7f51x1fZQoaAZHQGFBeSB9TgloB03oA2gIR0CTQ7buc+aCdX2UKGgGR0BuZTPt2LYPaAdNpQJoCEdAk1NQuuieunV9lChoBkdAX+g5bQkX12gHTegDaAhHQJNU0K5TZQJ1fZQoaAZHQGY28FyJbdJoB03oA2gIR0CTVUCbMHKPdX2UKGgGR0BfcsSf16E8aAdN6ANoCEdAk11ifthNNHV9lChoBkdAWQTzpX6qKmgHTegDaAhHQJNd9rbg0j11fZQoaAZHQGOCr74zrNZoB03oA2gIR0CTZ7bJfYz0dX2UKGgGR0BksToGIKtxaAdN6ANoCEdAk288A7xNI3V9lChoBkdAZqcskpqh12gHTegDaAhHQJNvjSgGr0d1fZQoaAZHQGX6IaUA1eloB03oA2gIR0CTcA5oGpuNdX2UKGgGR0BiQShew9q2aAdN6ANoCEdAk3CTB/I8yXV9lChoBkdAYBoSIxgy/WgHTegDaAhHQJNxLxG2Cul1fZQoaAZHQGSzQIt16mhoB03oA2gIR0CThpr3j+72dX2UKGgGR0Bk7hcmjTKDaAdN6ANoCEdAk4eZnxri2nV9lChoBkdAZeQgctGutGgHTegDaAhHQJOPHsv7FbV1fZQoaAZHQFslRoRIz31oB03oA2gIR0CTlFm65Gz9dX2UKGgGR0Buce1ndweeaAdNOgJoCEdAk5Rzafzz3HV9lChoBkdAYp9bKzRhMWgHTegDaAhHQJOWIeq7yx11fZQoaAZHQGJWMqJ/G2loB03oA2gIR0CTp08VYZEVdX2UKGgGR0BwDU52hZhbaAdN1wJoCEdAk6jx0Qsf73V9lChoBkdAX3/AzpHI62gHTegDaAhHQJOo9dhRZU11fZQoaAZHQGL2eVkc0choB03oA2gIR0CTqWaePJaJdX2UKGgGR0BgR94mkWRBaAdN6ANoCEdAk7FMa86FNHV9lChoBkdAZayOkLx7RmgHTegDaAhHQJPBe+nIhhZ1fZQoaAZHQGKiz67/XGxoB03oA2gIR0CTwdZJTVDsdX2UKGgGR0BcIwmNR3vAaAdN6ANoCEdAk8Jid4FA3XV9lChoBkdAZyjsniNsFmgHTegDaAhHQJPDDQTmGM51fZQoaAZHQFm/ACnxaxJoB03oA2gIR0CTxA/Aj6eodX2UKGgGR0BgZqdat9x7aAdN6ANoCEdAk9vIYzi0fHV9lChoBkdAXMwdyT6i02gHTegDaAhHQJPc85aNdZ91fZQoaAZHQELZQXQ+lj5oB0vkaAhHQJPjmA+Y+jd1fZQoaAZHQGJW/IsAeaNoB03oA2gIR0CT5Xtw71ZldX2UKGgGR0Bioy1b7j1gaAdN6ANoCEdAk+o9U0elsXV9lChoBkdAYMZ9bX6InGgHTegDaAhHQJPqT+717IF1fZQoaAZHQGCl3o1UEPloB03oA2gIR0CT645imVJMdX2UKGgGR0Bjt6+Yc/+saAdN6ANoCEdAk/2BQemvXHV9lChoBkdAZWz+LFXJYGgHTegDaAhHQJP/KC2+fyx1fZQoaAZHQGGDtiQT239oB03oA2gIR0CT/ytXgccVdX2UKGgGR0BibQfnwG4aaAdN6ANoCEdAk/+dJSR8t3V9lChoBkdAYX6x8lXzUmgHTegDaAhHQJQHfrzGxUx1fZQoaAZHQCSKvC/GlyloB00IAWgIR0CUD4nHNorXdX2UKGgGR0AqVr/sE7nxaAdNEAFoCEdAlBAKQV9F4XV9lChoBkdAYeLNorWiDmgHTegDaAhHQJQWuWMS9M91fZQoaAZHQGS9Z9d/rjZoB03oA2gIR0CUFy7K7qY7dX2UKGgGR0AzCKaG5+YuaAdNAwFoCEdAlBdYFvAGjnV9lChoBkdAY7obzbvgFWgHTegDaAhHQJQXp66asp51fZQoaAZHQGGQuSfUWmBoB03oA2gIR0CUGEfwqiGndX2UKGgGR0BdF9XtBv74aAdN6ANoCEdAlC9CFPBSDXV9lChoBkdAYwXjFQ2uPmgHTegDaAhHQJQwNOvdM0x1fZQoaAZHQGLEUc4o7V9oB03oA2gIR0CUNZzfaYeDdX2UKGgGR0BhdO5MDfWMaAdN6ANoCEdAlDcn5JsfrHV9lChoBkdAFu4Ju2qkumgHTSABaAhHQJQ5gN6PbPB1fZQoaAZHQGX/1JlJ6IFoB03oA2gIR0CUOyJ0nw5OdX2UKGgGR0BaqmDlHSWraAdN6ANoCEdAlDsx5cC5mXV9lChoBkdAX0uRdQfp2WgHTegDaAhHQJQ8RQm/nGN1fZQoaAZHQGCLXQdCE6FoB03oA2gIR0CUSlTS9du6dX2UKGgGR0BjSqPfbblBaAdN6ANoCEdAlEw81sLv1HV9lChoBkdAbGuXpnpSrGgHTQUDaAhHQJRX+9L6DXh1fZQoaAZHQGErxMN+b3JoB03oA2gIR0CUXt9tdiUgdX2UKGgGR0BwdhN9H+ZPaAdNKQJoCEdAlF7/7BO58XV9lChoBkdAZqJ/6wdKd2gHTegDaAhHQJRfVLBbfP51fZQoaAZHQF/JmLLpzLhoB03oA2gIR0CUZWm+0w8GdX2UKGgGR0BjQ2nVG0/oaAdN6ANoCEdAlGXbbcoH9nV9lChoBkdAYtbbA1vVE2gHTegDaAhHQJRm5WQwK0F1fZQoaAZHQGIil1B+nZVoB03oA2gIR0CUaft1IRRNdWUu"}, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "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:f3c999b1d6b699e88830a9807a76e9eef3bc6bfe7bf9a24c32e8b4f55eb440d5
+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 0x7aa6ec505080>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7aa6ec505120>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7aa6ec5051c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7aa6ec505260>",
+        "_build": "<function ActorCriticPolicy._build at 0x7aa6ec505300>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7aa6ec5053a0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7aa6ec505440>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7aa6ec5054e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7aa6ec505580>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7aa6ec505620>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7aa6ec5056c0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7aa6ec505760>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7aa6ec664200>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1740382909223304330,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "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 sha256:0d780073e2f2c2a0d1a4042c3e2f3bb26823b2b6a867a9336020b5c54d4e736d
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e17c2040a3dd0602f518260edfe7097599d8f402302ac0bec1c97bccfe1f9442
+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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.11.11
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.5.1+cu124
+- GPU Enabled: True
+- Numpy: 1.26.4
+- 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 sha256:9834b3bd3c71ea759ea54a6a75d6d025361a07cec2f15bd458db1fbf455f9ec6
+size 191038

results.json

@@ -0,0 +1 @@
+{"mean_reward": 243.0752002293219, "std_reward": 19.820664592875048, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-02-24T08:03:49.866309"}