Upload PPO LunarLander-v2 agent trained for 2e6 timesteps with n_envs = 32

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard 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 +1,28 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 274.57 +/- 19.54
+      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
+  

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 0x7fb648cc0ef0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb648cc0f80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb648cc7050>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb648cc70e0>", "_build": "<function ActorCriticPolicy._build at 0x7fb648cc7170>", "forward": "<function ActorCriticPolicy.forward at 0x7fb648cc7200>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb648cc7290>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb648cc7320>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb648cc73b0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb648cc7440>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb648cc74d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fb648c8f960>"}, "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": 32, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652481817.085761, "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="}, "_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": 310, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "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 sha256:3deabdb00f118aba4ce66bbeee011957ac30a9deb39fe48b5b0425b788c2e387
+size 144684

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.0

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 0x7fb648cc0ef0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb648cc0f80>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb648cc7050>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb648cc70e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fb648cc7170>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fb648cc7200>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb648cc7290>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fb648cc7320>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb648cc73b0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb648cc7440>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb648cc74d0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fb648c8f960>"
+    },
+    "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": 32,
+    "num_timesteps": 2031616,
+    "_total_timesteps": 2000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1652481817.085761,
+    "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:": "gAWVkwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksghZSMAUOUdJRSlC4="
+    },
+    "_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": 310,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "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 sha256:4255c6fa95cc93c8875e750e2d2369661a59fa70bd2e960df9d3bc04324d8123
+size 84893

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5eea591131804040bd5d366354fe0f4abe161b72bae5c4303a55a23de6e96b4b
+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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.5.0
+PyTorch: 1.11.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a441f46d011a4f945e439aab59949e6327d8dab2dd2b2c6056908ed1f84d6be
+size 201068

results.json

@@ -0,0 +1 @@
+{"mean_reward": 274.57459570252047, "std_reward": 19.541315543109878, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-13T23:30:37.200201"}