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: 256.76 +/- 18.46
+      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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f92378a2dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f92378a2e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f92378a2ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f92378a2f70>", "_build": "<function ActorCriticPolicy._build at 0x7f92378a9040>", "forward": "<function ActorCriticPolicy.forward at 0x7f92378a90d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f92378a9160>", "_predict": "<function ActorCriticPolicy._predict at 0x7f92378a91f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f92378a9280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f92378a9310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f92378a93a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f923789bcc0>"}, "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": 1671168, "_total_timesteps": 1669593, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670799419539591418, "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": -0.0009433436771715265, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 306, "n_steps": 1024, "gamma": 0.9971444712072906, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 3, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:967ce9864b63382b1e3d896d7273fc9bc9582ccb4b970fdab4c604849d0c4dd9
+size 147188

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

ppo-LunarLander-v2/data

@@ -0,0 +1,94 @@
+{
+    "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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f92378a2dc0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f92378a2e50>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f92378a2ee0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f92378a2f70>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f92378a9040>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f92378a90d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f92378a9160>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f92378a91f0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f92378a9280>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f92378a9310>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f92378a93a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f923789bcc0>"
+    },
+    "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": 1671168,
+    "_total_timesteps": 1669593,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1670799419539591418,
+    "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": -0.0009433436771715265,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVXxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMILoz0orZZcECUhpRSlIwBbJRL+IwBdJRHQLn9BnX/YJ51fZQoaAZoCWgPQwgcti3KbONVQJSGlFKUaBVL3WgWR0C5/Qp9Vmz0dX2UKGgGaAloD0MILbXeb/TQcUCUhpRSlGgVTQwBaBZHQLn9GnPVurJ1fZQoaAZoCWgPQwj1oQvqW7dwQJSGlFKUaBVL/mgWR0C5/R5CBwuNdX2UKGgGaAloD0MISl6dY8CcbkCUhpRSlGgVTQABaBZHQLn9KPN3W4F1fZQoaAZoCWgPQwh8tDhjGHpxQJSGlFKUaBVNEgFoFkdAuf0wZLqUvHV9lChoBmgJaA9DCLCsNCnFX3FAlIaUUpRoFUv9aBZHQLn9tiMYMv11fZQoaAZoCWgPQwiUpdb7DY9xQJSGlFKUaBVNGgFoFkdAuf4CuuA7P3V9lChoBmgJaA9DCLQ5zm1CBG5AlIaUUpRoFU0QAWgWR0C5/ip31SOzdX2UKGgGaAloD0MIMc9KWjGTckCUhpRSlGgVTQgBaBZHQLn+XbTc6/91fZQoaAZoCWgPQwipa+19qopwQJSGlFKUaBVNCwFoFkdAuf51ggHNYHV9lChoBmgJaA9DCIC21awzGHBAlIaUUpRoFU0mAWgWR0C5/n5RGc4HdX2UKGgGaAloD0MIkj8YeC5WcECUhpRSlGgVTQQBaBZHQLn+hN2C/XZ1fZQoaAZoCWgPQwjYKOs3U6ZxQJSGlFKUaBVNGAFoFkdAuf6QBS1ma3V9lChoBmgJaA9DCNanHJMF4XJAlIaUUpRoFU0WAWgWR0C5/pXhGYrsdX2UKGgGaAloD0MIG2MnvMR2ckCUhpRSlGgVTR0BaBZHQLn+ybbUPQR1fZQoaAZoCWgPQwjd7A+UW5xxQJSGlFKUaBVNDgFoFkdAuf7dj2BatHV9lChoBmgJaA9DCBnJHqEmjXFAlIaUUpRoFUv2aBZHQLn+5hVlwtJ1fZQoaAZoCWgPQwidhT3tsHFxQJSGlFKUaBVNFAFoFkdAuf7rbGm1pnV9lChoBmgJaA9DCFdBDHRtynBAlIaUUpRoFU0KAWgWR0C5/u68Yht+dX2UKGgGaAloD0MIfvylRb02cUCUhpRSlGgVTQMBaBZHQLn+8ExIre91fZQoaAZoCWgPQwhznNuE+/JxQJSGlFKUaBVNIQFoFkdAuf8KA+Y+jnV9lChoBmgJaA9DCLCsNCmFLXBAlIaUUpRoFUv2aBZHQLn/WoV2zOZ1fZQoaAZoCWgPQwhHy4Eeqg9wQJSGlFKUaBVL+2gWR0C5/6fgJkXldX2UKGgGaAloD0MIDJBoAkUscECUhpRSlGgVS+1oFkdAuf+2ogmqpHV9lChoBmgJaA9DCKyPh747LXJAlIaUUpRoFUvpaBZHQLn/88IRh+h1fZQoaAZoCWgPQwgIPDCA8M1wQJSGlFKUaBVL62gWR0C6AAVCswL3dX2UKGgGaAloD0MIprbUQd6VcUCUhpRSlGgVS/5oFkdAugAjk/8l5XV9lChoBmgJaA9DCMU56ug4jXBAlIaUUpRoFU0OAWgWR0C6ACWj0tiAdX2UKGgGaAloD0MIJEil2FEjckCUhpRSlGgVTQgBaBZHQLoATCojv/l1fZQoaAZoCWgPQwh9JCU9jMxyQJSGlFKUaBVNDQFoFkdAugBP2Dg62nV9lChoBmgJaA9DCAvT9xrCm3FAlIaUUpRoFUvxaBZHQLoAe1pj+aV1fZQoaAZoCWgPQwidL/ZevLdwQJSGlFKUaBVNEAFoFkdAugCM2S+xnnV9lChoBmgJaA9DCL/WpUaofnBAlIaUUpRoFU0IAWgWR0C6AJia/h2odX2UKGgGaAloD0MIHSJuTmXockCUhpRSlGgVTQUBaBZHQLoAnqxTsIF1fZQoaAZoCWgPQwjN5nEYzPtyQJSGlFKUaBVNEQFoFkdAugCqPp6hQHV9lChoBmgJaA9DCIuKOJ2kmXBAlIaUUpRoFU0aAWgWR0C6AKrwnYxtdX2UKGgGaAloD0MIn1c89YgpcECUhpRSlGgVTR0BaBZHQLoA2C3w1BN1fZQoaAZoCWgPQwhLHk/LD4BQQJSGlFKUaBVLsGgWR0C6BJg00m+kdX2UKGgGaAloD0MIyLWhYtyEcUCUhpRSlGgVTSIBaBZHQLoEvdOqNqB1fZQoaAZoCWgPQwiX5lYI66JxQJSGlFKUaBVNJAFoFkdAugUPAi3XqnV9lChoBmgJaA9DCJYJv9TPamxAlIaUUpRoFUv5aBZHQLoFHdaMaS91fZQoaAZoCWgPQwgaijvepCRzQJSGlFKUaBVNDAFoFkdAugVb94u9OHV9lChoBmgJaA9DCKrVV1dFOHJAlIaUUpRoFU0AAWgWR0C6BW7433pOdX2UKGgGaAloD0MIYcPTK6U5cUCUhpRSlGgVTRYBaBZHQLoFcL6UJOZ1fZQoaAZoCWgPQwhqGD4iZnxxQJSGlFKUaBVNAwFoFkdAugV4AR02cnV9lChoBmgJaA9DCDP60XAKL3JAlIaUUpRoFU1aAWgWR0C6BX7w8W9EdX2UKGgGaAloD0MItK88SI/dckCUhpRSlGgVS/xoFkdAugWnSeAd4nV9lChoBmgJaA9DCHpQUIqW6nJAlIaUUpRoFU0IAWgWR0C6Bava11GLdX2UKGgGaAloD0MImzqPiv99ckCUhpRSlGgVTQMBaBZHQLoF0o60Y0l1fZQoaAZoCWgPQwhb7swEwxZvQJSGlFKUaBVNHgFoFkdAugXzueBg/nV9lChoBmgJaA9DCML6P4d5AnJAlIaUUpRoFUv2aBZHQLoF+YfW+XZ1fZQoaAZoCWgPQwjytPzAFSRyQJSGlFKUaBVNKwFoFkdAugYBwYLsr3V9lChoBmgJaA9DCMkiTbxD+nFAlIaUUpRoFU0oAWgWR0C6BhCwW3z+dX2UKGgGaAloD0MI/tZOlARmcECUhpRSlGgVS/1oFkdAugY1V7x/eHV9lChoBmgJaA9DCLBYw0VuznBAlIaUUpRoFU0JAWgWR0C6BnHTNMXadX2UKGgGaAloD0MIH7qgvmVJb0CUhpRSlGgVS+NoFkdAugaO/7BO6HV9lChoBmgJaA9DCAJhp1h1f3BAlIaUUpRoFU0UAWgWR0C6BtSqIacadX2UKGgGaAloD0MIONkG7kAZcUCUhpRSlGgVS/RoFkdAugb968g6l3V9lChoBmgJaA9DCEUr9wKz9nJAlIaUUpRoFU0AAWgWR0C6BwHeFcptdX2UKGgGaAloD0MIUBpqFJJSckCUhpRSlGgVS/xoFkdAugcUyWRigHV9lChoBmgJaA9DCAb2mEjpHnNAlIaUUpRoFUv8aBZHQLoHG2alUId1fZQoaAZoCWgPQwiryykBcU5xQJSGlFKUaBVL8GgWR0C6BzOx0MgEdX2UKGgGaAloD0MINSVZh2Oxc0CUhpRSlGgVTRUBaBZHQLoHNdSEUTN1fZQoaAZoCWgPQwip9ul4zDJvQJSGlFKUaBVNDAFoFkdAugdbALy+YnV9lChoBmgJaA9DCBTP2QLCV3BAlIaUUpRoFU0AAWgWR0C6B3Ep3HJcdX2UKGgGaAloD0MIgUI9fYRGcECUhpRSlGgVS/doFkdAugeFgpjMFHV9lChoBmgJaA9DCOAsJcvJL25AlIaUUpRoFUv0aBZHQLoHiQ/X5Fh1fZQoaAZoCWgPQwgzpmCNc2xxQJSGlFKUaBVNBAFoFkdAugetaOgg5nV9lChoBmgJaA9DCOuPMAwYaHJAlIaUUpRoFU0gAWgWR0C6B7pBC2MLdX2UKGgGaAloD0MIe6AVGDIsbkCUhpRSlGgVS/poFkdAugfEpb2US3V9lChoBmgJaA9DCP5l9+ShgnFAlIaUUpRoFU0RAWgWR0C6CCWUOd5IdX2UKGgGaAloD0MI44kgzkN2bUCUhpRSlGgVTQsBaBZHQLoIO4GD+R51fZQoaAZoCWgPQwihD5axoRFJQJSGlFKUaBVLz2gWR0C6CHlHavicdX2UKGgGaAloD0MIcHhBRGpfb0CUhpRSlGgVS/xoFkdAugiUhaC+UXV9lChoBmgJaA9DCD2CGylboXBAlIaUUpRoFU0EAWgWR0C6CJ/8/D+BdX2UKGgGaAloD0MII4Wy8PUnb0CUhpRSlGgVTRkBaBZHQLoIn/ATIvJ1fZQoaAZoCWgPQwh72XbamjpzQJSGlFKUaBVNBQFoFkdAugi1oYekpXV9lChoBmgJaA9DCBA7U+g8SG5AlIaUUpRoFU0NAWgWR0C6CMg71ZkkdX2UKGgGaAloD0MI7UeKyLC4cECUhpRSlGgVTREBaBZHQLoI6TmGM4t1fZQoaAZoCWgPQwi7ufjbHvNuQJSGlFKUaBVL+2gWR0C6CO1RtP56dX2UKGgGaAloD0MIUDdQ4F03cUCUhpRSlGgVS+5oFkdAugk25qdpZnV9lChoBmgJaA9DCF4UPfAxYnBAlIaUUpRoFU0MAWgWR0C6CTmMCLdfdX2UKGgGaAloD0MIAkht4mTccECUhpRSlGgVTR8BaBZHQLoJQsg+yJN1fZQoaAZoCWgPQwhJgQUwpedyQJSGlFKUaBVNOQFoFkdAugmEBltj1HV9lChoBmgJaA9DCIQOuoSDCHFAlIaUUpRoFU0VAWgWR0C6CY8POIIodX2UKGgGaAloD0MIc2Tll4FUcUCUhpRSlGgVTSABaBZHQLoJk9RrJsB1fZQoaAZoCWgPQwjLK9fbZk5xQJSGlFKUaBVNBQFoFkdAugnTJfYzznV9lChoBmgJaA9DCDKuuDgqQ3NAlIaUUpRoFU0AAWgWR0C6Cd9tuUD/dX2UKGgGaAloD0MILNZwkXveQ0CUhpRSlGgVS8poFkdAugn3uE25x3V9lChoBmgJaA9DCNYaSu1FyXBAlIaUUpRoFUv4aBZHQLoKJzK9wm51fZQoaAZoCWgPQwiphCf0ui5wQJSGlFKUaBVNEQFoFkdAugo5x2jfvXV9lChoBmgJaA9DCH6oNGLmzXBAlIaUUpRoFUvwaBZHQLoKUdV/+bV1fZQoaAZoCWgPQwicielC7KBwQJSGlFKUaBVNDwFoFkdAugpajM3ZPHV9lChoBmgJaA9DCPhQoiUPrXBAlIaUUpRoFU0fAWgWR0C6CnQ/1QIldX2UKGgGaAloD0MI8iTpmkkNb0CUhpRSlGgVS/NoFkdAugp5YGMXJ3V9lChoBmgJaA9DCE29bhFYEXBAlIaUUpRoFU0WAWgWR0C6CrPczqKQdX2UKGgGaAloD0MIwHrct9oIcECUhpRSlGgVS+1oFkdAugq4QPI4l3V9lChoBmgJaA9DCIqQup19TW9AlIaUUpRoFU0GAWgWR0C6CuESuhbodX2UKGgGaAloD0MIYTWWsDYjcECUhpRSlGgVTQcBaBZHQLoK7BP9DQZ1ZS4="
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 306,
+    "n_steps": 1024,
+    "gamma": 0.9971444712072906,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 3,
+    "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 sha256:5c975aafbf0f502858b4a8b2348694de662ae056c5609cd2d9685c667b228b83
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7043f3aff549c2c9470b2ec4eef90828f3bb5382c93a836619cd17d9b5b13dc2
+size 43201

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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.8.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu116
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 256.75640448006754, "std_reward": 18.456985224348873, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-11T23:25:13.662193"}