Push LunarLander-v2 Attempt 01

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: 271.79 +/- 12.25
+      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 0x7f34c28795e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f34c2879670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f34c2879700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f34c2879790>", "_build": "<function ActorCriticPolicy._build at 0x7f34c2879820>", "forward": "<function ActorCriticPolicy.forward at 0x7f34c28798b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f34c2879940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f34c28799d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f34c2879a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f34c2879af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f34c2879b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f34c286dcf0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1670435536459533663, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_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": 248, "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, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.15", "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 sha256:1a7c14944968169349683e605286a9f4a67565bc37090d2dd58c73eea02aa6a7
+size 147202

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 0x7f34c28795e0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f34c2879670>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f34c2879700>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f34c2879790>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f34c2879820>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f34c28798b0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f34c2879940>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f34c28799d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f34c2879a60>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f34c2879af0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f34c2879b80>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f34c286dcf0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
+        "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": 1670435536459533663,
+    "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": 248,
+    "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
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9f6000c7af80b05a79f6085a5bb80a787f6bf14371799581a10130340866afc7
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c14f4da40a4e6efbc307dbd01afcdbc2a06e415cd8d52e0185c67ac455c9a49b
+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: 3.8.15
+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": 271.7947510359687, "std_reward": 12.254893559142577, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-07T18:23:19.494793"}