Upload trained agent to Hub

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: 264.56 +/- 19.76
+      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 0x7fb5218a13a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb5218a1430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb5218a14c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb5218a1550>", "_build": "<function ActorCriticPolicy._build at 0x7fb5218a15e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fb5218a1670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb5218a1700>", "_predict": "<function ActorCriticPolicy._predict at 0x7fb5218a1790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb5218a1820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb5218a18b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb5218a1940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fb521899d50>"}, "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": 1672778970025717468, "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:d71e7f51a695b9a2a6c269a40fb936061da77db0619deadab70411c91cefd28f
+size 147326

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 0x7fb5218a13a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fb5218a1430>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fb5218a14c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fb5218a1550>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fb5218a15e0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fb5218a1670>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fb5218a1700>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fb5218a1790>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fb5218a1820>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fb5218a18b0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fb5218a1940>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fb521899d50>"
+    },
+    "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": 1672778970025717468,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAE1rVT7toLE/MC0NP42K/b6ZPVI+DgNLPQAAAAAAAAAA5pGQPb75gz/CYQE9vZfTvsZyiD0tAr08AAAAAAAAAAA6/2k+8qJ4P56z1z0zK86+wGsoPi783r0AAAAAAAAAAGoyvj4gV1A/Zkj3uzs3vL45RYM+O0zfvQAAAAAAAAAADdDvvcqqGj7S9Qg+vJdRvnUtfjzKzA29AAAAAAAAAACzo8Q9dnmPPzcqnz6V2Ae/w3GgParEID4AAAAAAAAAAGa9hTwKR3u7NxI3vgoqML76ODq8MLBJPwAAgD8AAAAAZsXTvSYcgT/PM569rHCfvpVCLr4KAJc8AAAAAAAAAAAzBYq92KA8PwqCyz35OsW+5GEwve7SED0AAAAAAAAAAIDuhr0L530/olR1vQB/j7512My9hC6RvAAAAAAAAAAAgOpvvkz30j5Ug5A+m0y6vmbmCLx2nfw9AAAAAAAAAACahCi9w7lUulKriLXRtM6wCwtLO7yxtzQAAIA/AACAP+adEL1sjoc/5POEvB8ypr5lomG9NKYyPQAAAAAAAAAAQ4iDvmXHYz8CzXs8pZ6gvqSmUb5+9tk9AAAAAAAAAACmcO+9A2dVP42eWbzN17K+wnzIvTWLLD0AAAAAAAAAADNPiD2jM049njuVviTlN77vnfG8JpZIvAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
+    },
+    "_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:d80ba1b3e814ad2695ed9a37a430fda97d1a9322b4bc429ba0d3cc296ac2ba81
+size 88057

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:73ddf93e0941772ea61a740006d7db2f25c225ca8e0bd32cfb1cb5a7b0aa82ba
+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": 264.5645270315745, "std_reward": 19.757005974725388, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-03T21:27:26.107302"}