Push PPO trained LunarLander agent v2

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: 251.53 +/- 14.93
+      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 0x7fd97b890430>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd97b8904c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd97b890550>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd97b8905e0>", "_build": "<function ActorCriticPolicy._build at 0x7fd97b890670>", "forward": "<function ActorCriticPolicy.forward at 0x7fd97b890700>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd97b890790>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd97b890820>", "_predict": "<function ActorCriticPolicy._predict at 0x7fd97b8908b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd97b890940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd97b8909d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd97b890a60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd97b88fa80>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679852270924746057, "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": 248, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.97, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

ppo-LunarLander-v2-v3.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb84838a914891f6ab3bd7680ed5e903352d5b4a30d8afba92054a9393c25495
+size 148130

ppo-LunarLander-v2-v3/_stable_baselines3_version

@@ -0,0 +1 @@
+1.7.0

ppo-LunarLander-v2-v3/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 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 0x7fd97b890430>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fd97b8904c0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fd97b890550>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fd97b8905e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fd97b890670>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fd97b890700>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fd97b890790>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fd97b890820>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fd97b8908b0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fd97b890940>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fd97b8909d0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fd97b890a60>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fd97b88fa80>"
+    },
+    "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": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1679852270924746057,
+    "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": 248,
+    "n_steps": 1024,
+    "gamma": 0.999,
+    "gae_lambda": 0.97,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 128,
+    "n_epochs": 8,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

ppo-LunarLander-v2-v3/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:83fd42ada151050f3ccabe6167d720f4dafd14c4169885e497c95e74fe6bdf82
+size 87929

ppo-LunarLander-v2-v3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ca9ee7959e0c5ebc1d6182f31ec0389f62b8bfddb652b60def394fb6121330f6
+size 43393

ppo-LunarLander-v2-v3/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2-v3/system_info.txt

@@ -0,0 +1,7 @@
+- OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.9.16
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.22.4
+- Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 251.5320016508127, "std_reward": 14.933772504789413, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-26T18:01:33.641359"}