Upload PPO LunarLander-v2 trained agent

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: 237.55 +/- 21.77
+      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 0x7ff9429bf010>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff9429bf0a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff9429bf130>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff9429bf1c0>", "_build": "<function ActorCriticPolicy._build at 0x7ff9429bf250>", "forward": "<function ActorCriticPolicy.forward at 0x7ff9429bf2e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff9429bf370>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff9429bf400>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff9429bf490>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff9429bf520>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff9429bf5b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff9429bf640>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ff9432ce580>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711101580690412299, "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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"}, "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": "2.2.1+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:c13916010bea4ee64dff8e755e348590003ccc33aed6e9ce15ce41150eb32091
+size 148080

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 0x7ff9429bf010>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff9429bf0a0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff9429bf130>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff9429bf1c0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ff9429bf250>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ff9429bf2e0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff9429bf370>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff9429bf400>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ff9429bf490>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff9429bf520>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff9429bf5b0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff9429bf640>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7ff9432ce580>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1711101580690412299,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAKZ4oz0DiXK8OGRhvleSMr7QURY9koL6PgAAgD8AAIA/WiYuvloP4j5a7dc8BFFgvtVaJ72d6oa9AAAAAAAAAABt9wo+9vAtulSMSL4XVIS+jgGivNYJ77wAAAAAAAAAAM2kxjvh8/Q9a9ncPGlQhL6daX08Yvc2uwAAAAAAAAAAjdDJPcPZQ7ru9RG8Z1UettuynzpEYI01AAAAAAAAgD+AdCc9hXbau5/ZKTw1DYg8+FQ1PUbpZb0AAIA/AACAP2Ydm7yuXbC6iOJmNaDNNzCdMMg5wvigtAAAgD8AAIA/w4aCvscEHj9RRYg98Y+LvnhysL3mmc+8AAAAAAAAAADmn929y/rOPQm9Hj4kHXu+3gR1PEbCSL0AAAAAAAAAAKY91r3DBTa65j+CuiPWzrU7daQ7yRiYOQAAgD8AAAAAGqtCva6RkbpyS9S2oo2+sQAcLLj2T/k1AACAPwAAgD8oE4K++PKgP8jm3L6J7LW+jG56vnpvoL0AAAAAAAAAAI5SkL4V61Y/5JuxPT+Cj75+ULW9mt2VPQAAAAAAAAAAAIuzvHeJuD9ubrm+ll4lPkvOrDzg2TA9AAAAAAAAAADNTlO9SAmKuo2kjDQc9uCvrEgoOwJ3grMAAIA/AACAP1OtST5RrOc9vdudvrEnlr72yjK91RumPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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:": "gAWVQAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQCrHp2U0Nz+MAWyUS9yMAXSUR0CR+8jHn2ZidX2UKGgGR0BtyDwSamXPaAdNaQFoCEdAkfwoaYNRWXV9lChoBkdAcaSfJV81GmgHTRYBaAhHQJH9f6SDAah1fZQoaAZHQHJjM6mwaBJoB01PAWgIR0CR/6l7+kxidX2UKGgGR7//1J6IFeOXaAdNCgFoCEdAkf/dPxhDxHV9lChoBkdAcDm7Gecx02gHTXsBaAhHQJIAV7hNucd1fZQoaAZHQHGJF1bJOnFoB000AWgIR0CSAWw+MZP3dX2UKGgGR0BwRKj7ALy+aAdNUQFoCEdAkhXk2LpA2XV9lChoBkdAb87Qm/nGKmgHTUYBaAhHQJIWf1VYISl1fZQoaAZHQG9ViN0eU6hoB002AWgIR0CSGGymygPFdX2UKGgGR0ByC1I8QqZuaAdNRAFoCEdAkhiH9zfaYnV9lChoBkdAbcBq8DjioGgHTUwBaAhHQJIasqWkadd1fZQoaAZHQHFM6d6LOzJoB01TAWgIR0CSG5BhQWN4dX2UKGgGR0Bwh67iADq4aAdNQgFoCEdAkhwQYpDu0HV9lChoBkdAcEsXxOLzgGgHTT0BaAhHQJIcNweeWfN1fZQoaAZHQHC2ezposZpoB00HAWgIR0CSHk1TisGQdX2UKGgGR0BwmE7T2FnJaAdNWAFoCEdAkh5XDziCKHV9lChoBkdAb+bFy7wrlWgHTTcBaAhHQJIfPN+so2J1fZQoaAZHQG+R5J9RaX9oB01CAWgIR0CSH0XLvCuVdX2UKGgGR0BuOnQjUutfaAdNgwFoCEdAkiGHT7VJ+XV9lChoBkdAcBGqHXVbzWgHTUEBaAhHQJIij8iwB5p1fZQoaAZHQHAWFJ6IFeRoB00/AWgIR0CSIxndO6/ZdX2UKGgGR0BuasEcKgIyaAdN7AJoCEdAkiMlc2R7q3V9lChoBkdAZborZrYXf2gHTegDaAhHQJIjuj1wo9d1fZQoaAZHQGXWeglF+d9oB03oA2gIR0CSI9cwQDmsdX2UKGgGR0BvMHxYq5LAaAdNUgFoCEdAkiVY5ggHNXV9lChoBkdAbqOAksz2vmgHTWoBaAhHQJImRYPoV211fZQoaAZHQG5j4bsF+uxoB01HAWgIR0CSJt+fAbhndX2UKGgGR0BxJWzLOiWWaAdNPQFoCEdAkicyNfgJkXV9lChoBkdAcqZ9Jz1bq2gHTUwBaAhHQJIoDjvNNah1fZQoaAZHQB/IUahpQDVoB00VAWgIR0CSKBuNgjQidX2UKGgGR0BvgKqhlDneaAdNMAFoCEdAkijpiAlOXXV9lChoBkdAckp9LHuJDWgHTW8BaAhHQJIpLyI55qx1fZQoaAZHQG9QOHWSU1RoB00tAWgIR0CSKYWKdhAodX2UKGgGR0Bx89Kg7HQyaAdNVQFoCEdAkiq3hCMP0HV9lChoBkdAb26TNdJJ5GgHTUkBaAhHQJIu3HsC1Z11fZQoaAZHQHJMiKrJbMZoB01QAWgIR0CSMFgLZzxPdX2UKGgGR0Bwv4tWdVebaAdNaAFoCEdAkjILIDHOr3V9lChoBkdAcDH7fYSQHWgHTaoBaAhHQJIyPQSi/PB1fZQoaAZHQHGTPustCiRoB01MAWgIR0CSMxE2Hck/dX2UKGgGR0A6IZ4Oc2BKaAdNFQFoCEdAkjSgB1cMVnV9lChoBkdAbOehRqGlAWgHTa4BaAhHQJI07Dk2gnN1fZQoaAZHQHFW+HJtBOZoB01YAWgIR0CSNU6aLGaQdX2UKGgGR0BrgWdRR/EwaAdNWgFoCEdAkjYS2x6fJ3V9lChoBkdAcQ+RmK64D2gHTW0BaAhHQJI3LPZ7HAB1fZQoaAZHQHAYN9ph4MZoB01SAWgIR0CSNzezD4xldX2UKGgGR0BykLpdKNADaAdNWwFoCEdAkjlPlyR0VHV9lChoBkdAcJRNWU8mr2gHTUgBaAhHQJI6DqdH2AZ1fZQoaAZHQHHZgCwKSgZoB02AAWgIR0CSOjp0wJw9dX2UKGgGR0BuBpqbjLjhaAdNvwFoCEdAkjxAOz6acHV9lChoBkdActgeHi3ocWgHTUIBaAhHQJI9VzltCRh1fZQoaAZHQHMBki6g/TtoB007AWgIR0CST5I3zcyndX2UKGgGR0BuaafOD8LsaAdNOgFoCEdAklCkl/pdKXV9lChoBkdAb+eqfe1rqWgHTT4BaAhHQJJRjNC7btZ1fZQoaAZHQG7P9eQdS2poB00sAWgIR0CSUzhXr+o+dX2UKGgGR0ByGeNFSbYsaAdNUwFoCEdAklN57XxvvXV9lChoBkdAcGasYl6Z6WgHTYABaAhHQJJTp4FA3UB1fZQoaAZHQHGiViSaEzxoB01jAWgIR0CSVI7ALy+YdX2UKGgGR0BwvC+De0ojaAdNQQFoCEdAklU6Xa8HwHV9lChoBkdAb+LB9kSVW2gHTYQBaAhHQJJVljwx33Z1fZQoaAZHQHFfKVlf7aZoB01TAWgIR0CSVd2fTTfBdX2UKGgGR0BwmgHdGiHqaAdNEgFoCEdAklZa4H5aeXV9lChoBkdAa8a1Cw8nu2gHTUIBaAhHQJJXWMvRJEp1fZQoaAZHQHDH3DNyHVRoB01EAWgIR0CSWE1Q66redX2UKGgGR0BwCtZEDyOJaAdNQQFoCEdAkls94/u9e3V9lChoBkdAYfhu+AVfu2gHTegDaAhHQJJbxv73wkR1fZQoaAZHQHIRY/u9eyBoB01NAWgIR0CSXGsO5J9RdX2UKGgGR0Bv/j7sOXmeaAdNSQFoCEdAkl1I7/4qPXV9lChoBkdAbAi/ATIvJ2gHTZsBaAhHQJJd8mNR3vB1fZQoaAZHQG9aGEf1YhdoB00lAWgIR0CSXqtAcDKYdX2UKGgGR0Bwp3GACnxbaAdNTwFoCEdAkl64WHk92XV9lChoBkdAcectHQQcxWgHTSMBaAhHQJJe3K9wm3R1fZQoaAZHQHDi/boKUmloB007AWgIR0CSYBMkhRqHdX2UKGgGR0BtE9u5z5oHaAdNGQFoCEdAkmEcSwnpjnV9lChoBkdAcLwfiPyTZGgHTTYBaAhHQJJiBggHNX51fZQoaAZHQHC2xj4HooxoB01JAWgIR0CSYm9kjHGTdX2UKGgGR0By6j7oB7u2aAdNaQFoCEdAkmMdUXHim3V9lChoBkdAcelL8rI5pGgHTUcBaAhHQJJjr5Ec81Z1fZQoaAZHQHFFQ4S6DoRoB00uAWgIR0CSZPrRSgoPdX2UKGgGR0Bwp3ZIxxkvaAdNWQFoCEdAkmW9AX2ugnV9lChoBkdATMoN7SiM52gHS+doCEdAkmgX6InBtXV9lChoBkdAcmZG1x82JmgHTUEBaAhHQJJokUQCjlB1fZQoaAZHQHFXwn6VMVVoB00qAWgIR0CSaacLSeAedX2UKGgGR0BuI5kNFz+4aAdNMQFoCEdAkmpvlp48l3V9lChoBkdAcHYEKVpsXWgHTVYBaAhHQJJqmqlxffJ1fZQoaAZHQHKglEuxrzpoB01uAWgIR0CSat4Uvf0mdX2UKGgGR0BxI7q4YrJ9aAdNFAFoCEdAkmsmKyfL93V9lChoBkdAU19ZHNHH3mgHS/doCEdAkmv8XenAI3V9lChoBkdAcBLKTjebeGgHTRsBaAhHQJJsKQMhHLB1fZQoaAZHQHEoYZAIIGBoB01wAWgIR0CSbTVARkEtdX2UKGgGR0BxrrK5kK/maAdNJwFoCEdAkm6zuF6Av3V9lChoBkdAbGAf9P1tf2gHTUIBaAhHQJJvM5q/M4d1fZQoaAZHQG+qf7JnxrloB01kAWgIR0CSb3yAQQMAdX2UKGgGR0BrWATGo73gaAdNwwFoCEdAknAv779AHHV9lChoBkdAMFJdv863iWgHS95oCEdAknCA1WKdhHV9lChoBkdAa5S+B6KLsWgHTTUBaAhHQJJwrHCGetl1fZQoaAZHQHHrMm4RVZNoB001AWgIR0CScydwvQF+dX2UKGgGR0ByTNkYoAn2aAdNDwFoCEdAknNFKbrkbXV9lChoBkdAcQCD/EOy3WgHTSQBaAhHQJJ1Jj8UEgZ1fZQoaAZHQHGP0mdAgPpoB01GAWgIR0CSduQcPvrodWUu"
+    },
+    "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 sha256:59fc6aaa22af1f66ea7f63fc0105d550b6dd5cce67abb7393105ce7f5bf2620e
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3378d9e35bf0c8ecdd91c2dae54ed6e8d3561ffd0d8f11144a5a1a99d1ad6f42
+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: 2.2.1+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": 237.54817502672654, "std_reward": 21.772908035696215, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-22T10:27:43.415784"}