Uploading the trained agent --> PPO LunarLander-v2

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: 255.47 +/- 22.70
+      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 0x79a64a25b0a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79a64a25b130>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79a64a25b1c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79a64a25b250>", "_build": "<function ActorCriticPolicy._build at 0x79a64a25b2e0>", "forward": "<function ActorCriticPolicy.forward at 0x79a64a25b370>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79a64a25b400>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79a64a25b490>", "_predict": "<function ActorCriticPolicy._predict at 0x79a64a25b520>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79a64a25b5b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79a64a25b640>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79a64a25b6d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79a65391dc00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1717694231198285023, "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:": "gAWVQQwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGtLxK6FuemMAWyUTSoBjAF0lEdAmIFImCyyEHV9lChoBkdAcJJvc8DB/WgHTXwBaAhHQJiWZ7Y02tN1fZQoaAZHQGsxvc8DB/JoB01NAWgIR0CYmGk3CKrJdX2UKGgGR0BwE/+Q2dd3aAdNSwFoCEdAmJlZvP1L8XV9lChoBkdAcaD3rD63zGgHTToBaAhHQJiZ3gtOEdx1fZQoaAZHQHH2LbtZ3cJoB00rAWgIR0CYnR690zTGdX2UKGgGR0BxB73WWhRJaAdNQgFoCEdAmJ3ft6X0G3V9lChoBkdAcGMUm2LHdWgHTRYBaAhHQJigAm/nGKh1fZQoaAZHQHDwJOerdWRoB008AWgIR0CYoMsz2vjfdX2UKGgGR0BwUMk9lmOEaAdNJwFoCEdAmKHKdH2AXnV9lChoBkdAcoM1nM+u/2gHTU8BaAhHQJiiDerMkhR1fZQoaAZHQHBH48+zMRpoB00rAWgIR0CYook4WDYidX2UKGgGR0BtffvDxb0OaAdNmAFoCEdAmKLJXU6PsHV9lChoBkdAcucpeeFtbmgHTUkBaAhHQJii3gDRtxd1fZQoaAZHQG2Oar/82rJoB001AWgIR0CYoukleF+NdX2UKGgGR0Bugx+2E0zkaAdNNwFoCEdAmKSEGJN0vHV9lChoBkdAcQR9JSR8t2gHTS8CaAhHQJilWy7f51x1fZQoaAZHQF+kYNRWLgpoB03oA2gIR0CYpmef7JnydX2UKGgGR0BwNQsf7rLRaAdNNAFoCEdAmKa0vboKUnV9lChoBkdAb0qN2C/XXmgHTUUBaAhHQJim6Np/PPd1fZQoaAZHQG8Hh4MWoFVoB00iAWgIR0CYqI3fAKv3dX2UKGgGR0BxAA8HObAlaAdNSAFoCEdAmKmZJXhfjXV9lChoBkdAcjKzxwyZa2gHTakBaAhHQJipxrk8zRB1fZQoaAZHQHDW7/GVAzJoB00oAWgIR0CYqk/yoXKsdX2UKGgGR0BPXWSEDhcaaAdL9GgIR0CYqtdSVGCqdX2UKGgGR0BsGnJxNqQBaAdNQwFoCEdAmKvBsMy8BnV9lChoBkdAbYGdEsrd32gHTUEBaAhHQJisjLJSzgN1fZQoaAZHQHKNX8TBZZBoB01BAWgIR0CYrMTho/RmdX2UKGgGR0Bwk/yVfNRnaAdNPwFoCEdAmK0kOy3TeHV9lChoBkdAbcRZmI0qIGgHTT4BaAhHQJitcWxhUip1fZQoaAZHQHAluT7l7t1oB01DAWgIR0CYrXpZwGW2dX2UKGgGR0Bso1OoHcDbaAdNFQFoCEdAmK7C35N47nV9lChoBkdAcZQ5YYBNmGgHTQgBaAhHQJivpZwGW2R1fZQoaAZHQHBqULDye7NoB01TAWgIR0CYr9BuGbkPdX2UKGgGR0BwYCgXdj5LaAdNHgFoCEdAmLAEKE3843V9lChoBkdAQIEeCCjDbmgHS/JoCEdAmLCsTWXkYHV9lChoBkdAciKRKpT/AGgHTTYBaAhHQJixLrs0HhV1fZQoaAZHQDXsQPI4lyBoB0v7aAhHQJiyrQOWjXZ1fZQoaAZHQHGYNxIatLdoB00eAWgIR0CYsrwj+rEMdX2UKGgGR0Bus0DQqqffaAdNGwFoCEdAmLMpCfHxSnV9lChoBkdAcO0SGJvYOGgHTRABaAhHQJi0IHkcS5B1fZQoaAZHQHEYuRLbpNdoB01mAWgIR0CYtSSVnmJWdX2UKGgGR0ByZs7IT4+KaAdNHAFoCEdAmLWIKYzBRHV9lChoBkdAb7IWt2cJ+mgHTRoBaAhHQJi11fD1oQF1fZQoaAZHQHIScRtgrpdoB00vAWgIR0CYtfiR4hUzdX2UKGgGR0BwmiucMEzPaAdNQAFoCEdAmLdS8WbgCXV9lChoBkdAchHJkXk5qGgHTVkBaAhHQJi4RrM1TBJ1fZQoaAZHQHFlBE0BOpNoB00iAWgIR0CYuNGRV6u5dX2UKGgGR0BxqUuBczInaAdNHAFoCEdAmLjQS8J2MnV9lChoBkdAcqTDK5kK/mgHTVkBaAhHQJi5/DaXa8J1fZQoaAZHQHGkVcMVk+ZoB00xAWgIR0CYz045Lh73dX2UKGgGR0BwwD6+FlCkaAdNYgFoCEdAmM/D2JzkqHV9lChoBkdAb5rrs0HhTGgHTXABaAhHQJjRl8stkFx1fZQoaAZHQG6BYmTkhidoB01KAWgIR0CY0xvmYBvKdX2UKGgGR0BwTlo371qWaAdNQAFoCEdAmNNvitJWenV9lChoBkdAcIL/eLvTgGgHTVkBaAhHQJjT66GxlhB1fZQoaAZHQG0vm/336ARoB01JAWgIR0CY1Q/lyR0VdX2UKGgGR0ByhUB+4LCvaAdNGAFoCEdAmNUTg2qDLHV9lChoBkdAcEVQGwA2h2gHTSQBaAhHQJjVMGZ/kNp1fZQoaAZHQHLMTDjzZpVoB01JAWgIR0CY1f24d6sydX2UKGgGR0BykQ8TzundaAdNHAFoCEdAmNa8B2fTTnV9lChoBkdAcCNaMaS9umgHTSgBaAhHQJjX+gte2NN1fZQoaAZHQHKI5amoBJZoB01DAWgIR0CY2XKqn3tbdX2UKGgGR0BwNxYmsvIwaAdNoQFoCEdAmNnJyhi9ZnV9lChoBkdAcqYV+I/JNmgHTU4BaAhHQJjZ3KT0QK91fZQoaAZHQHJsuKfnOjZoB00vAWgIR0CY2xTlkpZwdX2UKGgGR0BwlG2Yv38GaAdNOAFoCEdAmNunmq5sj3V9lChoBkdAcP2m5UcXFmgHTUUBaAhHQJjdb2RJVbR1fZQoaAZHQHEDLROUMXtoB00dAWgIR0CY3azMibDudX2UKGgGR0BvHQ2Q4jrzaAdNKgFoCEdAmN3LpJPIn3V9lChoBkdAcv2704BFNWgHTQ8BaAhHQJjeO6f8Mux1fZQoaAZHQHC25CngpBpoB01CAWgIR0CY3l9fTkQxdX2UKGgGR0BxSPux8lXzaAdNOgFoCEdAmN+r7oB7u3V9lChoBkdAcQmTIvJzUGgHTSgBaAhHQJjgEfGMn7Z1fZQoaAZHQG9Ohs67ulZoB01dAWgIR0CY4O8eS0SidX2UKGgGR0ByXWVlf7aaaAdNDAFoCEdAmOEW3z+WGHV9lChoBkdAcg5xbSqlxmgHTVABaAhHQJjiAdBBzFN1fZQoaAZHQHCiiu2Zy+9oB00wAWgIR0CY5AcGC7K8dX2UKGgGR0BxkW3fAKv3aAdNPgFoCEdAmOQhFuvU0HV9lChoBkdAcWjQQtjCpGgHTT4BaAhHQJjkcdlum791fZQoaAZHQG9CKdH2AXloB000AWgIR0CY5WwBo24vdX2UKGgGR0Bv18O/cnE3aAdNBgFoCEdAmOaCfQKKHnV9lChoBkdAcRMl3hXKbWgHTR4BaAhHQJjnFvrGBFx1fZQoaAZHQG9FcENe+mFoB00iAWgIR0CY529PUKAsdX2UKGgGR0BwuNzBAOawaAdNFQFoCEdAmOeHVbzK93V9lChoBkdAcBOuEmICVGgHTW4BaAhHQJjoBfgJkXl1fZQoaAZHQHARvf0mMOxoB004AWgIR0CY6LcZccENdX2UKGgGR0Bv7VqL0jC6aAdNIgFoCEdAmOkya3I+4nV9lChoBkdAb0R003wTd2gHTTgBaAhHQJjqKqWC2+h1fZQoaAZHQG12Ahr30wtoB00hAWgIR0CY6kdCmdiEdX2UKGgGR0BxYbCyhSLqaAdNHgFoCEdAmOpX4Glhw3V9lChoBkdAbQ26WgOBlWgHTSoBaAhHQJjri2w3YL91fZQoaAZHQHF9vI8yN4toB001AWgIR0CY7emhM8HOdX2UKGgGR0Bw9zxH5JsgaAdNaAFoCEdAmPAm3WnTAnV9lChoBkdAbQ1UZNwiq2gHTUkBaAhHQJjwdSLqD9R1fZQoaAZHQHBDaYVqN6xoB01oAWgIR0CY8IqagElmdX2UKGgGR0BwJni83++/aAdNLAFoCEdAmPCQWWQfZHV9lChoBkdAcTcDGLk0amgHTRQBaAhHQJjws2jwhGJ1fZQoaAZHQGLUvS2H+IdoB03oA2gIR0CY8Qs7MgU2dX2UKGgGR0Bxt5YRujynaAdNKgFoCEdAmPFL04BFNXVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 284, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.26.2"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:579bce2303fdd05d329e8bb0a36209f41962f247e8840fa7811a6b3efab681af
+size 148084

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 0x79a64a25b0a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79a64a25b130>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79a64a25b1c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79a64a25b250>",
+        "_build": "<function ActorCriticPolicy._build at 0x79a64a25b2e0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x79a64a25b370>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x79a64a25b400>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79a64a25b490>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x79a64a25b520>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79a64a25b5b0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79a64a25b640>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x79a64a25b6d0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x79a65391dc00>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1717694231198285023,
+    "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": 284,
+    "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:a0d069a06c377f34de95d2c80d8bea80115a0125709f5e644a73313cf70dc49b
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:169e94740fe90be70891e832f1b34b4bbb27d7b7c8c8c9314fdfe0439967c8d1
+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 Sun Apr 28 14:29:16 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.3.0+cu121
+- GPU Enabled: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.26.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 255.47159060000004, "std_reward": 22.702584355165044, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-06T17:43:56.645379"}