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: 253.21 +/- 15.73
+      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 0x7fcde1a14790>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcde1a14820>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcde1a148b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcde1a14940>", "_build": "<function ActorCriticPolicy._build at 0x7fcde1a149d0>", "forward": "<function ActorCriticPolicy.forward at 0x7fcde1a14a60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcde1a14af0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcde1a14b80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcde1a14c10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcde1a14ca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcde1a14d30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcde1a150c0>"}, "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": 1671078900300500479, "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, "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 sha256:0b2a45787f0a9f94eb20a6052596d45693125ccba55d34e94acc49c97ab06b08
+size 147210

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 0x7fcde1a14790>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcde1a14820>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcde1a148b0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcde1a14940>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fcde1a149d0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fcde1a14a60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcde1a14af0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fcde1a14b80>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcde1a14c10>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcde1a14ca0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcde1a14d30>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fcde1a150c0>"
+    },
+    "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": 1671078900300500479,
+    "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
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1f6ad2e9e5150c91db9f9f53299e4e884a8f8680945b80326ee0d5554c8a571d
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4d1e8e65f270e957848059383f97c57243d571b243fa87172224c1ddc2e6d686
+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": 253.20503501168452, "std_reward": 15.734212984783825, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-15T05:16:57.572248"}