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: 259.15 +/- 17.26
+      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 0x7f7d61e7c550>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7d61e7c5e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7d61e7c670>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7d61e7c700>", "_build": "<function ActorCriticPolicy._build at 0x7f7d61e7c790>", "forward": "<function ActorCriticPolicy.forward at 0x7f7d61e7c820>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7d61e7c8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7d61e7c940>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7d61e7c9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7d61e7ca60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7d61e7caf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7d61e7cb80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f7d61ef8270>"}, "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": 1676833647809032947, "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-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+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 sha256:75513ad27bdbe98c5469d5a81101c0f751a282e7afee3bef2ea7ae1f1ae6036c
+size 147420

ppo-LunarLander-v2/_stable_baselines3_version

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

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 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 0x7f7d61e7c550>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7d61e7c5e0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7d61e7c670>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7d61e7c700>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f7d61e7c790>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f7d61e7c820>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7d61e7c8b0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7d61e7c940>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f7d61e7c9d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7d61e7ca60>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7d61e7caf0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7d61e7cb80>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f7d61ef8270>"
+    },
+    "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": 1676833647809032947,
+    "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:c31c0c9345424c1e52ad543adabeca6d5d7f8a3caf44e5cd3717aa00bd96129c
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a6aaaf6afe5b0e515288f14b8438c6ddd20df0546c98b9029dc19b24b00bf11f
+size 43393

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-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.8.10
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1+cu116
+- GPU Enabled: True
+- Numpy: 1.21.6
+- Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 259.15353612333337, "std_reward": 17.256083912299637, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-19T19:32:25.443811"}