Upload PPO LunarLander-v2 trained agent

.gitattributes

@@ -30,3 +30,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 231.87 +/- 65.97
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+# **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 0x7fc953a5c620>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc953a5c6a8>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc953a5c730>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc953a5c7b8>", "_build": "<function ActorCriticPolicy._build at 0x7fc953a5c840>", "forward": "<function ActorCriticPolicy.forward at 0x7fc953a5c8c8>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc953a5c950>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc953a5c9d8>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc953a5ca60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc953a5cae8>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc953a5cb70>", "__abstractmethods__": "frozenset()", "_abc_registry": "<_weakrefset.WeakSet object at 0x7fc953ad0ba8>", "_abc_cache": "<_weakrefset.WeakSet object at 0x7fc953ad0be0>", "_abc_negative_cache": "<_weakrefset.WeakSet object at 0x7fc953ad0c18>", "_abc_negative_cache_version": 59}, "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:": "gAWVhwAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZSMBWR0eXBllJOUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=", "n": 4, "shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "seed": null, "action_noise": null, "start_time": 1664887094.491341, "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": 124, "n_steps": 2048, "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:": "gAWV7wIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxgL2hvbWUvc2hvYWliL21pbmljb25kYTMvZW52cy9zdHVkeS9saWIvcHl0aG9uMy42L3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxgL2hvbWUvc2hvYWliL21pbmljb25kYTMvZW52cy9zdHVkeS9saWIvcHl0aG9uMy42L3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "target_kl": null, "system_info": {"OS": "Linux-5.15.0-48-generic-x86_64-with-debian-bullseye-sid #54~20.04.1-Ubuntu SMP Thu Sep 1 16:17:26 UTC 2022", "Python": "3.6.13", "Stable-Baselines3": "1.3.0", "PyTorch": "1.10.1+cu111", "GPU Enabled": "True", "Numpy": "1.19.5", "Gym": "0.19.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08ba7b5702edbec8ff7038305a4459abb2d1dee3c20464fe09135f94cd6f1d80
+size 144342

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.3.0

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 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 0x7fc953a5c620>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc953a5c6a8>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc953a5c730>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc953a5c7b8>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fc953a5c840>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fc953a5c8c8>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc953a5c950>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fc953a5c9d8>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc953a5ca60>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc953a5cae8>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc953a5cb70>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_registry": "<_weakrefset.WeakSet object at 0x7fc953ad0ba8>",
+        "_abc_cache": "<_weakrefset.WeakSet object at 0x7fc953ad0be0>",
+        "_abc_negative_cache": "<_weakrefset.WeakSet object at 0x7fc953ad0c18>",
+        "_abc_negative_cache_version": 59
+    },
+    "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:": "gAWVhwAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZSMBWR0eXBllJOUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=",
+        "n": 4,
+        "shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1664887094.491341,
+    "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": 124,
+    "n_steps": 2048,
+    "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,
+    "target_kl": null
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e73e1f6f1e936f5fc3d3ba40286d767fd702efd4895c20c7659010ce32d3b910
+size 84829

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0548044f8e4471ed89f9b73e20571f2f058aa057b8ee19990185b3fe3ff05cb9
+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-5.15.0-48-generic-x86_64-with-debian-bullseye-sid #54~20.04.1-Ubuntu SMP Thu Sep 1 16:17:26 UTC 2022
+Python: 3.6.13
+Stable-Baselines3: 1.3.0
+PyTorch: 1.10.1+cu111
+GPU Enabled: True
+Numpy: 1.19.5
+Gym: 0.19.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 231.86512012816192, "std_reward": 65.9667555955851, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-04T15:48:37.841958"}