Added LunarLander-v2 agent model trained with PPO

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: 264.47 +/- 25.30
+      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 0x7ffa0374e820>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ffa0374e8b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ffa0374e940>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ffa0374e9d0>", "_build": "<function ActorCriticPolicy._build at 0x7ffa0374ea60>", "forward": "<function ActorCriticPolicy.forward at 0x7ffa0374eaf0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ffa0374eb80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ffa0374ec10>", "_predict": "<function ActorCriticPolicy._predict at 0x7ffa0374eca0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ffa0374ed30>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ffa0374edc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ffa0374ee50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ffa037499c0>"}, "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": 1674069996829137786, "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 sha256:25822dc4cc3ab6b24c01f3172b78e992f8354c68875542f25d51cf7999b40d85
+size 147384

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 0x7ffa0374e820>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ffa0374e8b0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ffa0374e940>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ffa0374e9d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ffa0374ea60>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ffa0374eaf0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ffa0374eb80>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ffa0374ec10>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ffa0374eca0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ffa0374ed30>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ffa0374edc0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ffa0374ee50>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7ffa037499c0>"
+    },
+    "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": 1674069996829137786,
+    "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 sha256:0d9641177d4187cd4597ed2412a8b746f2d489d86ec007572761b74bdb0205ac
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:429c1268785d0110e54b6ffe2d2e14946663f2019445b92ed8e281bed4112cfe
+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": 264.4745956095455, "std_reward": 25.295127615642368, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-18T20:21:49.574379"}