Uploading the PPO agent for LunarLander-v2 environment

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: 261.49 +/- 32.45
+      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 0x7f565f9ff550>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f565f9ff5e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f565f9ff670>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f565f9ff700>", "_build": "<function ActorCriticPolicy._build at 0x7f565f9ff790>", "forward": "<function ActorCriticPolicy.forward at 0x7f565f9ff820>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f565f9ff8b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f565f9ff940>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f565f9ff9d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f565f9ffa60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f565f9ffaf0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f565f9fb3f0>"}, "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": 2506752, "_total_timesteps": 2500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671620429429405176, "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": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 612, "n_steps": 1024, "gamma": 0.998, "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:bb5b3293fd2c2b7c96b0de9feb0bb1d06ca609b5588c26983e3ea43576dfa585
+size 147095

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 0x7f565f9ff550>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f565f9ff5e0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f565f9ff670>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f565f9ff700>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f565f9ff790>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f565f9ff820>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f565f9ff8b0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f565f9ff940>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f565f9ff9d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f565f9ffa60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f565f9ffaf0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f565f9fb3f0>"
+    },
+    "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": 2506752,
+    "_total_timesteps": 2500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1671620429429405176,
+    "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": -0.0027007999999999477,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 612,
+    "n_steps": 1024,
+    "gamma": 0.998,
+    "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 sha256:3a2c245573d0541dfad7c1a35e42b48f9fbc77b2b91491b6425078fd3317936d
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ac6086608fc2c813c939ec4e0ff52695483f5a7a73cfc64a8186cacd18b9f1a1
+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": 261.49364884233245, "std_reward": 32.45082178040339, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-21T11:43:36.820288"}