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: 262.09 +/- 23.12
+      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 0x7f6e1df89dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6e1df89e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6e1df89ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6e1df89f70>", "_build": "<function ActorCriticPolicy._build at 0x7f6e1df8f040>", "forward": "<function ActorCriticPolicy.forward at 0x7f6e1df8f0d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6e1df8f160>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6e1df8f1f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6e1df8f280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6e1df8f310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6e1df8f3a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f6e1df8c2d0>"}, "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": 1671572398249666944, "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:e8b888968ac24b85161251ed0e6e737f9fdcd0d4d1412d68a9d4034827499be9
+size 147218

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 0x7f6e1df89dc0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6e1df89e50>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6e1df89ee0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6e1df89f70>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f6e1df8f040>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f6e1df8f0d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6e1df8f160>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f6e1df8f1f0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6e1df8f280>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6e1df8f310>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6e1df8f3a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f6e1df8c2d0>"
+    },
+    "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": 1671572398249666944,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAA1HkD32RG26XRfnOn5bMTbbS4k73sIFugAAgD8AAIA/syrFPa4lhbo230g790laN2X6VjthdTa6AACAPwAAgD/mngS+x/FaP0hZ1rz14Y6+ajISvnBrvT0AAAAAAAAAALPfNT2PAg66bSYuulGW17SEvxE74MZNOQAAgD8AAIA/misePY9eb7oOIlk737cNN8QBWzsi6+o1AACAPwAAgD+agFi9e5KJumbOajsj4bQ3m/rFN+G+M7oAAIA/AACAP2YnML7w6/g+kLVfPuSmcb5y/wA9w4G+vQAAAAAAAAAAzZd1Pa61jrqVPO06Fau/Nfwe3Lq+rQm6AACAPwAAgD/mPG89wzlNupvxfjtVbfa0TAxrOS/klboAAIA/AAAAAJprpjzssYc4qAGmOaErjLZRqFO7kK3IuAAAgD8AAIA/ZsIIvexpgLlZDaA6VRV6NeUMobp4TL+5AACAPwAAgD9mRkU9SF+juujlMzvRspo1b25hOgyDTLoAAIA/AACAPyZV6D0lg5g+tvThPNk2iL6WXsQ8uNrlOwAAAAAAAAAAZgu5PZu0hD10+ye+AkNNvjvijTyov888AAAAAAAAAACaFOQ8j45Ouh6JjbvJABO2iOXGul6OpToAAIA/AACAPwD0CD3Xsxm5Ck7hu0O2qzUbatA5ttohtQAAgD8AAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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:e97242853c013d29cf269478483ee534621f2fcfafe894b60660ab6ec46d4d5c
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2197c69c48a3f160c798819430e21615c3a6e2840ebc79db72498223ce5d6e17
+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": 262.0868489546168, "std_reward": 23.1195720741405, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-20T22:09:56.392363"}