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: 280.16 +/- 13.38
+      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 0x784c59c1d3f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x784c59c1d480>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x784c59c1d510>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x784c59c1d5a0>", "_build": "<function ActorCriticPolicy._build at 0x784c59c1d630>", "forward": "<function ActorCriticPolicy.forward at 0x784c59c1d6c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x784c59c1d750>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x784c59c1d7e0>", "_predict": "<function ActorCriticPolicy._predict at 0x784c59c1d870>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x784c59c1d900>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x784c59c1d990>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x784c59c1da20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x784c59bc7e00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 3009900, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1696369866697263439, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVjAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYZAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxmFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0033000000000000806, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 474, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 25, "n_steps": 1524, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 74, "n_epochs": 6, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c1503353a528531f107c9fe9c9d0d2f4154f31392b7a26f1b35f8e7ba976f69a
+size 147024

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-LunarLander-v2/data

@@ -0,0 +1,99 @@
+{
+    "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 0x784c59c1d3f0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x784c59c1d480>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x784c59c1d510>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x784c59c1d5a0>",
+        "_build": "<function ActorCriticPolicy._build at 0x784c59c1d630>",
+        "forward": "<function ActorCriticPolicy.forward at 0x784c59c1d6c0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x784c59c1d750>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x784c59c1d7e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x784c59c1d870>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x784c59c1d900>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x784c59c1d990>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x784c59c1da20>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x784c59bc7e00>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 3009900,
+    "_total_timesteps": 3000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1696369866697263439,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVjAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYZAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxmFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.0033000000000000806,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 474,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_shape": [
+            8
+        ],
+        "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 25,
+    "n_steps": 1524,
+    "gamma": 0.999,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 74,
+    "n_epochs": 6,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:09c5afd7662cba33ddf1113b05cd0005d94425db97f28118a88412b2c1586f80
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:81c3d46b5f9b3034c28146dd069ef84105db08699b614d52be8aa540e33dedf2
+size 43329

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 +1,9 @@
+- OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.0.1+cu118
+- GPU Enabled: True
+- Numpy: 1.23.5
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 280.1582906629426, "std_reward": 13.380510815813322, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-10-03T22:48:46.103513"}