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: 271.64 +/- 11.36
+      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 0x7f9bba4df1f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9bba4df280>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9bba4df310>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9bba4df3a0>", "_build": "<function ActorCriticPolicy._build at 0x7f9bba4df430>", "forward": "<function ActorCriticPolicy.forward at 0x7f9bba4df4c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9bba4df550>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9bba4df5e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9bba4df670>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9bba4df700>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9bba4df790>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9bba4df820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f9bba4e01c0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679315088110788520, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29561d0f0c1257c8141efaed9dece5e7339d136a2fd42be14a23674f47366e29
+size 147308

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.7.0

ppo-LunarLander-v2/data

@@ -0,0 +1,95 @@
+{
+    "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 0x7f9bba4df1f0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9bba4df280>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9bba4df310>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9bba4df3a0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f9bba4df430>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f9bba4df4c0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9bba4df550>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9bba4df5e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f9bba4df670>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9bba4df700>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9bba4df790>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9bba4df820>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f9bba4e01c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        "n": 4,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1679315088110788520,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAGBUJL6DIVq8Bo4fu4rqjrlGZNQ9R5GDOgAAgD8AAIA/Gg6KPeHK6bqOixs83JWEPO1vEjweoGa9AACAPwAAgD/aaNQ9SC2Kum5EO7kWNKy3f/11uzOUXjgAAIA/AACAP0AfOr7vr2c/28bVvnbOIr9AH3++prsPvgAAAAAAAAAAYFANPoE1tbyoVFO91RgfPQiMIL4zJvQ9AACAPwAAgD8zJwq8JKScPVP9LD1xjXC+9WenutbF8zwAAAAAAAAAAHouAj6s1y4/Th+XPfvRF78hTR0+VQdDvQAAAAAAAAAA5cWUvk2F3T56q5k+3pYav53N1r6EUo8+AAAAAAAAAABezJe+d3c5Pxdghr68Fwu/Uqm8vqeQzLwAAAAAAAAAADM1Ezyula66p7m4O+cpRjyKBGa7lSMwPQAAgD8AAIA/837BPSvHpT3K2g2+9XBcvq2SQr07k3o8AAAAAAAAAAAT6y++qVB/vE1FmrtfYgy6SuvbPaMT4joAAIA/AACAP3qsLL6DlVi8k8kxOpk7HDixscI9/V5iuQAAgD8AAIA/CPvVvmbDXz8nHoS+ykIpv628BL9WeDw9AAAAAAAAAABACre97PGpuUUhK7VN0bewHmIcux5PWjQAAIA/AACAP83Y5LzPmVk9hTvkPTygV77Wo++8c23muwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVJxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIzt2ul2YdcECUhpRSlIwBbJRLvowBdJRHQJjty2b5M111fZQoaAZoCWgPQwi0OjlD8T9vQJSGlFKUaBVLqmgWR0CY7iPAwfyPdX2UKGgGaAloD0MIwR9+/nvBcECUhpRSlGgVS8NoFkdAmO6JZGKAKHV9lChoBmgJaA9DCNzUQPO5BnFAlIaUUpRoFUuoaBZHQJjuzGsFMZh1fZQoaAZoCWgPQwiZDwh0ZuFxQJSGlFKUaBVL4mgWR0CY7/vVmSQpdX2UKGgGaAloD0MI198SgH+Vc0CUhpRSlGgVS9BoFkdAmPB+uvECNnV9lChoBmgJaA9DCHSWWYSiSHFAlIaUUpRoFU0uAWgWR0CY8IyMUAT7dX2UKGgGaAloD0MI1zOEY9bwcECUhpRSlGgVS61oFkdAmPD/JeVs13V9lChoBmgJaA9DCIv/O6ICI3NAlIaUUpRoFUvwaBZHQJjxKOWBz3h1fZQoaAZoCWgPQwjnGJC9XjByQJSGlFKUaBVL1mgWR0CY8hcO9WZJdX2UKGgGaAloD0MIo1huabWCckCUhpRSlGgVS9VoFkdAmPI9XtBv73V9lChoBmgJaA9DCHHIBtJF7mVAlIaUUpRoFU3oA2gWR0CY8rlIEr5JdX2UKGgGaAloD0MIsfojDAMWbkCUhpRSlGgVS71oFkdAmPLfxc3VC3V9lChoBmgJaA9DCFSQn43cwm9AlIaUUpRoFUuyaBZHQJjzboFFDv51fZQoaAZoCWgPQwgK98q8VQZyQJSGlFKUaBVLzGgWR0CY89OPvKEGdX2UKGgGaAloD0MIDtqrj8cAc0CUhpRSlGgVTRQBaBZHQJj0KkM1CPZ1fZQoaAZoCWgPQwhW1GAahqJzQJSGlFKUaBVLymgWR0CY9UK/mDDkdX2UKGgGaAloD0MIcvp6vmY1SECUhpRSlGgVS3JoFkdAmPZnwPRRdnV9lChoBmgJaA9DCAfTMHzEE3JAlIaUUpRoFUvCaBZHQJj2vCCSRr91fZQoaAZoCWgPQwgjFcYWQrhwQJSGlFKUaBVNAwFoFkdAmPcU5ZKWcHV9lChoBmgJaA9DCPYmhuSkx3BAlIaUUpRoFUu6aBZHQJj3PeZXuE51fZQoaAZoCWgPQwiaXfdWJGtvQJSGlFKUaBVLrmgWR0CY96h/y5I6dX2UKGgGaAloD0MIM4l6weeJcUCUhpRSlGgVS89oFkdAmPftOARTTHV9lChoBmgJaA9DCHu+Zrnssm9AlIaUUpRoFUvEaBZHQJj4RVMmF8J1fZQoaAZoCWgPQwgHlbiOcf1yQJSGlFKUaBVLzWgWR0CY+aABT4tZdX2UKGgGaAloD0MI/tR46aY+ckCUhpRSlGgVS9doFkdAmPrKguh9LHV9lChoBmgJaA9DCE91yM0w3XBAlIaUUpRoFUutaBZHQJj6y6lLvkR1fZQoaAZoCWgPQwiZ1qaxvZtxQJSGlFKUaBVL52gWR0CY+6cE/0NCdX2UKGgGaAloD0MI33AfuXWvcUCUhpRSlGgVS7VoFkdAmPxxV+7UX3V9lChoBmgJaA9DCDpZar1fI3JAlIaUUpRoFUveaBZHQJj8hM7EHdJ1fZQoaAZoCWgPQwhdpibBm0tzQJSGlFKUaBVL62gWR0CY/JBAfMfSdX2UKGgGaAloD0MIBn+/mK0Ac0CUhpRSlGgVS6loFkdAmP6BA4XGfnV9lChoBmgJaA9DCLgCCvV0L3NAlIaUUpRoFUvFaBZHQJj+rd0q6OJ1fZQoaAZoCWgPQwhFKowtxORxQJSGlFKUaBVL0mgWR0CY/t2hIvrXdX2UKGgGaAloD0MIG/Slt78ockCUhpRSlGgVS9hoFkdAmQAFnqVyFXV9lChoBmgJaA9DCCCYo8fvmXJAlIaUUpRoFUvDaBZHQJkAXu0CzTp1fZQoaAZoCWgPQwhbfAqA8fVwQJSGlFKUaBVL9GgWR0CZAR4REnb7dX2UKGgGaAloD0MIDFwea4a5c0CUhpRSlGgVS/poFkdAmQJszVMEinV9lChoBmgJaA9DCBx6i4d3C3FAlIaUUpRoFUvVaBZHQJkC2+lCTll1fZQoaAZoCWgPQwhXJvxS/31yQJSGlFKUaBVLm2gWR0CZAygk1MufdX2UKGgGaAloD0MIa7jIPV03cUCUhpRSlGgVS8JoFkdAmQMzBdld1XV9lChoBmgJaA9DCPkSKjj8pXFAlIaUUpRoFUvWaBZHQJkEBp35eqt1fZQoaAZoCWgPQwgfhetReO5wQJSGlFKUaBVLuWgWR0CZBHu3c580dX2UKGgGaAloD0MI/dgkP2KLcUCUhpRSlGgVS6poFkdAmQXNFfAsTXV9lChoBmgJaA9DCJzfMNHgJ3FAlIaUUpRoFUvwaBZHQJkF6mtQsPJ1fZQoaAZoCWgPQwhA+bt3VAtyQJSGlFKUaBVL42gWR0CZBjIMSbpedX2UKGgGaAloD0MInaG44435cECUhpRSlGgVS79oFkdAmQbYwdsBQ3V9lChoBmgJaA9DCJ6xL9n4125AlIaUUpRoFUu+aBZHQJkG/Mmnfl91fZQoaAZoCWgPQwipF3yaE1FwQJSGlFKUaBVLtGgWR0CZB6EPlMh6dX2UKGgGaAloD0MIfXbAdYW5cECUhpRSlGgVS8loFkdAmQgBUm2LHnV9lChoBmgJaA9DCFJ+Uu1TGXBAlIaUUpRoFUuxaBZHQJkIAduHerN1fZQoaAZoCWgPQwiK5CuBlIZvQJSGlFKUaBVLtmgWR0CZCVm+0w8GdX2UKGgGaAloD0MIKEhsd48MYkCUhpRSlGgVTegDaBZHQJkJww9JSR91fZQoaAZoCWgPQwh9yjFZXMJvQJSGlFKUaBVLx2gWR0CZCdNfgJkYdX2UKGgGaAloD0MI38Mlxx1/bkCUhpRSlGgVS7toFkdAmQoKSkj5bnV9lChoBmgJaA9DCBAHCVH+aHJAlIaUUpRoFUveaBZHQJkKNhw2l2x1fZQoaAZoCWgPQwg9t9CVCNNkQJSGlFKUaBVN6ANoFkdAmQphpL26CnV9lChoBmgJaA9DCOrQ6Xm3IHNAlIaUUpRoFUvxaBZHQJkKbZ8KG+N1fZQoaAZoCWgPQwiEDOTZ5ddxQJSGlFKUaBVLn2gWR0CZCmhBZ6lddX2UKGgGaAloD0MIrU1jey10ckCUhpRSlGgVS8VoFkdAmQqG2Xsw+XV9lChoBmgJaA9DCKTfvg6cw3BAlIaUUpRoFUu9aBZHQJkLiK+BYmt1fZQoaAZoCWgPQwgsDJHT1+5xQJSGlFKUaBVL2WgWR0CZC67K7qY7dX2UKGgGaAloD0MIi+B/K9l5ckCUhpRSlGgVS9NoFkdAmQwzqSowVXV9lChoBmgJaA9DCGPshJdga29AlIaUUpRoFUu5aBZHQJkMfi3ocJd1fZQoaAZoCWgPQwg0EqER7KtyQJSGlFKUaBVNAQFoFkdAmQzTufEn9nV9lChoBmgJaA9DCH5TWKlgV3NAlIaUUpRoFUvraBZHQJkNqdK/VRV1fZQoaAZoCWgPQwgB+n3/ZmpxQJSGlFKUaBVLqGgWR0CZDbHBDXvqdX2UKGgGaAloD0MIhWBVvXwjc0CUhpRSlGgVS69oFkdAmQ3RDCxeLXV9lChoBmgJaA9DCESF6uaiH3FAlIaUUpRoFUvXaBZHQJkOcSrYGt91fZQoaAZoCWgPQwjKNnAHKttxQJSGlFKUaBVLr2gWR0CZDpgmqo60dX2UKGgGaAloD0MI+HE0R5b/ckCUhpRSlGgVS7VoFkdAmQ6Y2S+xnnV9lChoBmgJaA9DCOTYeoZwkG5AlIaUUpRoFUvCaBZHQJkO369CeEt1fZQoaAZoCWgPQwg34zRElQhzQJSGlFKUaBVLyWgWR0CZDxOCXhOydX2UKGgGaAloD0MIFEGch9MhckCUhpRSlGgVS+9oFkdAmQ+4cinpCHV9lChoBmgJaA9DCFiQZiyalXJAlIaUUpRoFU0iAWgWR0CZEMgm7aqTdX2UKGgGaAloD0MI2AxwQXZPcUCUhpRSlGgVS8VoFkdAmRDbj5sTFnV9lChoBmgJaA9DCGQjEK8rkHJAlIaUUpRoFUvKaBZHQJkRRgqmTDB1fZQoaAZoCWgPQwg5uHTM+RFwQJSGlFKUaBVLwGgWR0CZEV8ox59mdX2UKGgGaAloD0MIIJkOnZ6MckCUhpRSlGgVS/1oFkdAmRHAo9cKPXV9lChoBmgJaA9DCA4WTtJ87HFAlIaUUpRoFU0CAWgWR0CZEbiKziS8dX2UKGgGaAloD0MIZylZTkLycECUhpRSlGgVS7JoFkdAmRHkVzp5eXV9lChoBmgJaA9DCEI+6NlsFHJAlIaUUpRoFUvJaBZHQJkShjRUm2N1fZQoaAZoCWgPQwh/L4UHDSRyQJSGlFKUaBVL2GgWR0CZEr3vx6OYdX2UKGgGaAloD0MI/bypSIXQckCUhpRSlGgVS7xoFkdAmRL2VZ9uxnV9lChoBmgJaA9DCE5k5gIXcHBAlIaUUpRoFUvdaBZHQJkTljslb/x1fZQoaAZoCWgPQwjzyvW2WThyQJSGlFKUaBVLzWgWR0CZE6HKOktVdX2UKGgGaAloD0MI2AsFbMcNcUCUhpRSlGgVS8loFkdAmRO+G0u14XV9lChoBmgJaA9DCHptNlaiHXNAlIaUUpRoFU0AAWgWR0CZFHt3OfNBdX2UKGgGaAloD0MIVP1K58MFbkCUhpRSlGgVS6hoFkdAmRSxaTwDvHV9lChoBmgJaA9DCJ60cFlF1HJAlIaUUpRoFUv1aBZHQJkVYCq6vq11fZQoaAZoCWgPQwiIDRZO0upwQJSGlFKUaBVL0WgWR0CZFZDVH4GmdX2UKGgGaAloD0MIR5OLMbAxcUCUhpRSlGgVS8JoFkdAmRWs7lq8DnV9lChoBmgJaA9DCPhPN1DgMXFAlIaUUpRoFUu4aBZHQJkWCYw7DEZ1fZQoaAZoCWgPQwgogjgP59dxQJSGlFKUaBVL1WgWR0CZFoJ3xFy8dX2UKGgGaAloD0MIIhecwZ/gcECUhpRSlGgVS7toFkdAmRbD6rNnoXV9lChoBmgJaA9DCHtq9dWVUnNAlIaUUpRoFUvTaBZHQJkXmYBvJil1fZQoaAZoCWgPQwh8SPjenzZxQJSGlFKUaBVL0WgWR0CZF8SEDhcadX2UKGgGaAloD0MIlj/fFixCcECUhpRSlGgVS8BoFkdAmRgvHPu5SXV9lChoBmgJaA9DCEjElEgiWW9AlIaUUpRoFUvGaBZHQJkYNr6+FlF1fZQoaAZoCWgPQwhSnnk5bHJvQJSGlFKUaBVLqmgWR0CZGK6Ae7tidWUu"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 310,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:03b93ecc9a96594a87d2cbfb94c10b20d6ef56b24f9d7042afcc066af302dd13
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:789c984731e3d4f2caeaeeb83b9e15ecc193054fb8923f45ccf58579232c4192
+size 43393

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,7 @@
+- OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.9.16
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.22.4
+- Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 271.6396855748539, "std_reward": 11.355473939663382, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-20T12:52:28.813020"}