test

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: 238.38 +/- 36.51
+      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 0x7de5b0723d90>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7de5b0723e20>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7de5b0723eb0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7de5b0723f40>", "_build": "<function ActorCriticPolicy._build at 0x7de5b0734040>", "forward": "<function ActorCriticPolicy.forward at 0x7de5b07340d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7de5b0734160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7de5b07341f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7de5b0734280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7de5b0734310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7de5b07343a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7de5b0734430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7de5b0730940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708929243077396539, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAPMvoL32uGK6xQFVud5DV7TOUHE71UB6OAAAgD8AAIA/zbyuuj2UF7soloS7UehePI9lPjznKkO9AACAPwAAgD8zIXc8pDJcPCJk5zy17VK++2PyPBiY2bwAAAAAAAAAAGacgj32PGO6WDwcugH7jLbbW7u6j0QCNgAAgD8AAIA/M5zhvBTMlbpAAM86gJS9NZo5bToNku+5AACAPwAAgD+a32Y8vYQhPxo1PL3qPHq+pguLO6r6Bb0AAAAAAAAAAJrHFD2Pklm6AwFou8Mjh7YF5hI7huyFOgAAgD8AAIA/gFWzva7Lh7rt0+g40xamNAlWMTuQOw64AACAPwAAgD+aZR68j4JyusqsVbl11jy0gqgGuzpLejgAAIA/AACAP3NiI752oCK8LTEOO3qV7zjFyYw9W/I0ugAAgD8AAIA/M5/cPfxegT8O4I49JvyBvhEYjTxFHgA8AAAAAAAAAACaLHO9z4ohvOFnILzElAY85RiNvd477TwAAIA/AACAP+YyQD2uKY26YHvdOp7fqjVGZXI6TV4AugAAgD8AAIA/M8ctPMMRbLpWEju87Eaitoxa0zr9GxQ2AACAPwAAgD/NERg9Kax8uqM7XbtKj4w4bC8QO30fvTkAAIA/AACAP2Y2qj3sOey5tmmbu2+QHbaFU6y7lYGRNQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "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:aab358b4d73a5f4ff091105b8a21ed101b435f81a09e1f25acd8fc99e5322c8e
+size 148088

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 0x7de5b0723d90>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7de5b0723e20>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7de5b0723eb0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7de5b0723f40>",
+        "_build": "<function ActorCriticPolicy._build at 0x7de5b0734040>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7de5b07340d0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7de5b0734160>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7de5b07341f0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7de5b0734280>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7de5b0734310>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7de5b07343a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7de5b0734430>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7de5b0730940>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1708929243077396539,
+    "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:": "gAWVRAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQFyMi+tbLU2MAWyUTegDjAF0lEdAkvAygPEsKHV9lChoBkdAYaCkWykbgmgHTegDaAhHQJLw/BeokzJ1fZQoaAZHQGApw79ycTdoB03oA2gIR0CS8vkIX0oSdX2UKGgGR0BjgDMFEAo5aAdN6ANoCEdAkvM4mgJ1JXV9lChoBkdAXPguL74zrWgHTegDaAhHQJLz9xffGdZ1fZQoaAZHQGPbD5TIeYFoB03oA2gIR0CS9TMNc4YKdX2UKGgGR0BhX5pBX0XhaAdN6ANoCEdAkvXyJfpljHV9lChoBkdAZmonkT6BRWgHTegDaAhHQJMEj5YYBNp1fZQoaAZHQGCztIK+i8FoB03oA2gIR0CTCPsByS3cdX2UKGgGR0BfvlzdUKiPaAdN6ANoCEdAkw66V2Rq5HV9lChoBkdAYrt1W8yvcWgHTegDaAhHQJMQBhYvFm51fZQoaAZHQGDhR4yGi6BoB03oA2gIR0CTEgBWxQizdX2UKGgGR0BkypLGrCFcaAdN6ANoCEdAkxPmBFuvU3V9lChoBkdAZLdEVFhG6WgHTegDaAhHQJMX6kfs/pt1fZQoaAZHQGGnd/SYw7FoB03oA2gIR0CTGjk5IYm+dX2UKGgGR0BZ1rjHXEqEaAdN6ANoCEdAkzFau4gA63V9lChoBkdATdVnTRYzSGgHTSEBaAhHQJM8VC+lCTl1fZQoaAZHQGT9jQAuIyloB03oA2gIR0CTP8j6N2kjdX2UKGgGR0BjLIYaYNRWaAdN6ANoCEdAk0CYY77sOXV9lChoBkdAYFS3Kji4rmgHTegDaAhHQJNCxWHUMG51fZQoaAZHQGTbJSBK+SNoB03oA2gIR0CTQwUI9kjHdX2UKGgGR0Bg/eTs6aLGaAdN6ANoCEdAk0PN0JWvKXV9lChoBkdAZTh76YVqOGgHTegDaAhHQJNFFfb9If91fZQoaAZHQF3D2iL2pQ1oB03oA2gIR0CTRekcjqwAdX2UKGgGR0BhP0SM98qnaAdN6ANoCEdAk1SSFbmlqXV9lChoBkdAYu7h8YyftmgHTegDaAhHQJNYB1MdtEZ1fZQoaAZHQGWLa8Yht+FoB03oA2gIR0CTXWaL4vexdX2UKGgGR0BhKbRc/t6YaAdN6ANoCEdAk17DUNKAa3V9lChoBkdAZFkVYZEUkGgHTegDaAhHQJNgwlRgqmV1fZQoaAZHQGbuJSBK+SNoB03oA2gIR0CTYpBZpztDdX2UKGgGR0BiAE4YJmdzaAdN6ANoCEdAk2qnCKrJbXV9lChoBkdAYoa0uUUwjGgHTegDaAhHQJOCluTA31l1fZQoaAZHQGWQxiPQv6FoB03oA2gIR0CTi2MbFS88dX2UKGgGR0Bjul6JIlMRaAdN6ANoCEdAk47RSHdoFnV9lChoBkdAY6RRUm2LHmgHTegDaAhHQJOPlP69CeF1fZQoaAZHQGM7v1L8JldoB03oA2gIR0CTkcGD+R5kdX2UKGgGR0Bkal+RYA80aAdN6ANoCEdAk5IBBVuJlHV9lChoBkdAZdVYbKifx2gHTegDaAhHQJOSx/gBLf11fZQoaAZHQGRWrjHXEqFoB03oA2gIR0CTlBMAWBSUdX2UKGgGR0BWpx9G7SRbaAdN6ANoCEdAk5TUqYqoZXV9lChoBkdAZgdd1uBMBmgHTegDaAhHQJOl6uoxYaJ1fZQoaAZHQGD6/WUbDMxoB03oA2gIR0CTqbFW4mTldX2UKGgGR0BhsaVpsXSCaAdN6ANoCEdAk69aWTot+XV9lChoBkdAYsaRxLkCFWgHTegDaAhHQJOwypiqhlF1fZQoaAZHQGCeJj2Bas9oB03oA2gIR0CTsvX4j8k2dX2UKGgGR0Bc6o2n889waAdN6ANoCEdAk7T7uIAOrnV9lChoBkdAYNJZU1hsqWgHTegDaAhHQJO7lu2qkuZ1fZQoaAZHQGROoCEHt4RoB03oA2gIR0CTwk6wdKdydX2UKGgGR0BiGUvduYQbaAdN6ANoCEdAk95fR7Z393V9lChoBkdAYrxMQmNR32gHTegDaAhHQJPhyveP7vZ1fZQoaAZHQGJdQg9vCMxoB03oA2gIR0CT4oCq6vq1dX2UKGgGR0Bg2QSteUpvaAdN6ANoCEdAk+R/ppvgnHV9lChoBkdAZS0b+cYqG2gHTegDaAhHQJPkvwLE1l51fZQoaAZHQF0wDmr8zhxoB03oA2gIR0CT5YBp5/smdX2UKGgGR0Bjz4rH2h7FaAdN6ANoCEdAk+aya/h2n3V9lChoBkdAXrpqubI91WgHTegDaAhHQJPngDs+mnB1fZQoaAZHQGriSDh99c9oB02lAmgIR0CT6thtLteEdX2UKGgGR0Bhx4jIJZ4faAdN6ANoCEdAk/Y4J/oaDXV9lChoBkdAYkZjOLR8dGgHTegDaAhHQJP7ADq4YrJ1fZQoaAZHQGWEMguAZsNoB03oA2gIR0CUAynV5KODdX2UKGgGR0Bf8oSxqwhXaAdN6ANoCEdAlAWFWGRFJHV9lChoBkdAYfMpvxYq5WgHTegDaAhHQJQHvf8/D+B1fZQoaAZHQGPFLpqynk1oB03oA2gIR0CUDprGipNsdX2UKGgGR0Blo10tAcDKaAdN6ANoCEdAlBUXT/hl2HV9lChoBkdAYglSIgvDg2gHTegDaAhHQJQwe7wrlNl1fZQoaAZHQGRdnmzSkTJoB03oA2gIR0CUM8jRlYlqdX2UKGgGR0BZGuXNTtLMaAdN6ANoCEdAlDSDJdSl33V9lChoBkdAZNdpKzzErGgHTegDaAhHQJQ2dZ6lchV1fZQoaAZHQGGnlVcUuctoB03oA2gIR0CUNrFzuF6BdX2UKGgGR0Bi3C+xnnMdaAdN6ANoCEdAlDdfrB0p3HV9lChoBkdAX7tRYRujymgHTegDaAhHQJQ4gfeUILR1fZQoaAZHQF5G/6fra/RoB03oA2gIR0CUOTKxLTQWdX2UKGgGR0BivDPdEb5uaAdN6ANoCEdAlDyJ1zQu3HV9lChoBkdAUFTCBPKuCGgHTQABaAhHQJREewGGEf11fZQoaAZHQGU+N7BwdbRoB03oA2gIR0CURzxiXpnpdX2UKGgGR0BhxPhOxjaxaAdN6ANoCEdAlErQYUFjeHV9lChoBkdAZr56vaDf32gHTegDaAhHQJRR+nvUjLV1fZQoaAZHQF6mSU1Q66toB03oA2gIR0CUVGlbNbC8dX2UKGgGR0BwVLdznzQNaAdN3QFoCEdAlFZI+jdpI3V9lChoBkdAY3oyzHCGe2gHTegDaAhHQJRW6rLhaTx1fZQoaAZHQGe1RigCfYloB03oA2gIR0CUYCo99tuUdX2UKGgGR0BgZV0cOskqaAdN6ANoCEdAlGd7ytmthnV9lChoBkdAb0LmYBvJimgHTXMDaAhHQJR96N0eU6h1fZQoaAZHQGJDnerMkhRoB03oA2gIR0CUgTkqMFUydX2UKGgGR0BciCHZbpu/aAdN6ANoCEdAlISFajesP3V9lChoBkdAYQEg/TspomgHTegDaAhHQJSHXj7yhBZ1fZQoaAZHQF88cQiA2AJoB03oA2gIR0CUh62aDwpfdX2UKGgGR0BlcJGFzuF6aAdN6ANoCEdAlIpU7W/ag3V9lChoBkdAYFMcPvrnkmgHTegDaAhHQJSQGxD9fkZ1fZQoaAZHQGRSxIatLctoB03oA2gIR0CUmC3wkPc0dX2UKGgGR0BiKUEPlMh6aAdN6ANoCEdAlJq9UCJXQ3V9lChoBkdAcBfW8RL9M2gHTX4BaAhHQJSbztRekYZ1fZQoaAZHQGTb4AS39aVoB03oA2gIR0CUna8cuJ1rdX2UKGgGR0Bmyzrqt5lfaAdN6ANoCEdAlKNG/i5uqHV9lChoBkdAXfJXo1UEPmgHTegDaAhHQJSlJl6JIlN1fZQoaAZHQGIsB9Tgl4VoB03oA2gIR0CUpoi0OVgQdX2UKGgGR0A9+utOmBOIaAdNBQFoCEdAlKaXnZCfH3V9lChoBkdAaOf7AtWdVmgHTegDaAhHQJSm27Wd3B51fZQoaAZHQGN8bqptJnRoB03oA2gIR0CUrDedkJ8fdX2UKGgGR0Bd79U0elsQaAdN6ANoCEdAlLKRxo7FKnVlLg=="
+    },
+    "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:f40fb8d2c4c3d7fbc1b0240d15d7cfa38e6430fc5697f33428a87107f3486f5e
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:63bfe7a4773bf3a701aacbc5332c6b27fdfdc9da577a6585295b3acbeb8ec66e
+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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.1.0+cu121
+- GPU Enabled: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 238.3808247, "std_reward": 36.50523140322714, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-26T07:08:36.556781"}