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: 255.91 +/- 18.35
+      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 0x7b6386573eb0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b6386573f40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b6386580040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b63865800d0>", "_build": "<function ActorCriticPolicy._build at 0x7b6386580160>", "forward": "<function ActorCriticPolicy.forward at 0x7b63865801f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b6386580280>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b6386580310>", "_predict": "<function ActorCriticPolicy._predict at 0x7b63865803a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b6386580430>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b63865804c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b6386580550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b638671ae00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708058446842915076, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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:fe4635b2ba8d091d0406cea6818d44f81ea88a9d20111c70a17f8802db1aa93d
+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 0x7b6386573eb0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b6386573f40>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b6386580040>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b63865800d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7b6386580160>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7b63865801f0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b6386580280>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b6386580310>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7b63865803a0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b6386580430>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b63865804c0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b6386580550>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7b638671ae00>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1708058446842915076,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADOMlTwfM7U/hvRNPkvzir21M9I8cnkjPgAAAAAAAAAAAH1cvYXT5rmYFYU6k0+INdzl5DuuFaC5AACAPwAAgD8mWbs9IZ5FPvhFzL1Jboy+Ttntu+6xUD0AAAAAAAAAAM1s27v2kCq6YAQXOBEc/jH9RzC7xsostwAAgD8AAIA/AOAkPOEimLrZwkU72j7VNwRn7zqGlxS6AACAPwAAgD9ze5G916cEuxx0RzxJXGE8W+NHvNl3RT0AAIA/AACAP4BBc72Pplq6iKeutteTN7K6uTo7XdvINQAAgD8AAIA/JofSPfoKmz+LNOk9TrO9vvO5Dj49Aia9AAAAAAAAAACzQbI9KTgwukEYh7siFgy20dyYOxJ5pzoAAIA/AACAP2bGxTrOi4a8SmlivMoZljygC+u9FbBwPQAAgD8AAIA/TWUnvubpkT8eDB6/zPTxvpApJb2MgTC+AAAAAAAAAACac1y8FE7puCJyjrlcE4y1e+u5Oi5gpzgAAIA/AACAPwBg3DuPxhO6yqEvOIBfozItYNW6k49JtwAAgD8AAIA/AKSePKT3N7vfwRC6PuCUPOmthDyK+H+9AACAPwAAgD8AQum8uG7UuUCCW7yGHdc5YoYoO8bvu7oAAIA/AACAP2ZYoz24xo65Kj0DO56V9DYYKv25WpraNQAAgD8AAIA/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:": "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    },
+    "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:f863d09510fc689bac9dbe0164ef0d01cdb8b4a0f53ef5c5b790af71ed005e17
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6efa722f7210fe98fbaab51d6e9abe325b82468a50facbc5b9db98b74fa7972a
+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": 255.9075874, "std_reward": 18.351722128205708, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-16T05:36:06.825944"}