initial commit

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: 286.47 +/- 13.88
+      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 0x7fc5c4d3bee0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc5c4d3bf70>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc5c4d41040>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc5c4d410d0>", "_build": "<function ActorCriticPolicy._build at 0x7fc5c4d41160>", "forward": "<function ActorCriticPolicy.forward at 0x7fc5c4d411f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc5c4d41280>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc5c4d41310>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc5c4d413a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc5c4d41430>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc5c4d414c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fc5c4d34d50>"}, "verbose": 0, "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": 1671153590817953200, "learning_rate": 0.0007, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAQAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 0.95, "ent_coef": 0.0, "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-LubarLander-1M.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dfbaa0bc533940cf0727d3166a605132d65e305932c952ed6fd6451af506d362
+size 147097

ppo-LubarLander-1M/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

ppo-LubarLander-1M/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 0x7fc5c4d3bee0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc5c4d3bf70>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc5c4d41040>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc5c4d410d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fc5c4d41160>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fc5c4d411f0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc5c4d41280>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fc5c4d41310>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc5c4d413a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc5c4d41430>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc5c4d414c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fc5c4d34d50>"
+    },
+    "verbose": 0,
+    "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": 1671153590817953200,
+    "learning_rate": 0.0007,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAQAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 0.95,
+    "ent_coef": 0.0,
+    "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-LubarLander-1M/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f4b3b3b93fb15d7ca68b41c9c9c6f541179a5775a746d2ef1bfabb6eaf1f2d55
+size 87929

ppo-LubarLander-1M/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:943dbe0257e75b540a83b8a604a24d45ea5417e26fd79bbd0dbff0b466d21026
+size 43201

ppo-LubarLander-1M/pytorch_variables.pth

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

ppo-LubarLander-1M/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": 286.47366608585537, "std_reward": 13.877779077784506, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-16T01:36:05.211544"}