ppo-LunarLander-model

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: ppo-mlp
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 247.24 +/- 16.82
+      name: mean_reward
+      verified: false
+---
+
+# **ppo-mlp** Agent playing **LunarLander-v2**
+This is a trained model of a **ppo-mlp** 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 0x7fedd1083b50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fedd1083be0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fedd1083c70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fedd1083d00>", "_build": "<function ActorCriticPolicy._build at 0x7fedd1083d90>", "forward": "<function ActorCriticPolicy.forward at 0x7fedd1083e20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fedd1083eb0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fedd1083f40>", "_predict": "<function ActorCriticPolicy._predict at 0x7fedd1090040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fedd10900d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fedd1090160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fedd10901f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fedd10202c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1721138212443522938, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_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": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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:d6d6e20de32291b51b521325562c9f69b64938b53fb69b24636451b4d84cc4e0
+size 148088

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 0x7fedd1083b50>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fedd1083be0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fedd1083c70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fedd1083d00>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fedd1083d90>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fedd1083e20>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fedd1083eb0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fedd1083f40>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fedd1090040>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fedd10900d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fedd1090160>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fedd10901f0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fedd10202c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1721138212443522938,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJqAfr0E7qQ/0KXovnBzwL432pG828WzvQAAAAAAAAAALR9vPuPQ9j7gHqq9wBe8vvtc+z1YGtQ8AAAAAAAAAAAl8Jy+Yc2BPzJb/rxdizK+6YQhvjR5yj0AAAAAAAAAAPo7Gb6GXNU+mCNRPvG4S77kQY67rR72vQAAAAAAAAAAZr0CvQfCpz9+piW+wyyOvl2/Qr0VHB27AAAAAAAAAACz9A891PCxP/LP0T5dG1W+UgBSu8bf5T0AAAAAAAAAAKotgz7bThE/+bufvr2xO74q9XS9zMlCPQAAAAAAAAAAZuTBvHF8TrvWAjC8dhGOPCqKa7xib3Q9AACAPwAAgD/N0QM9G4DnPepNW77QFEe+Um+/var1IT0AAAAAAAAAAEYCAb6HkiM/uC7SPTP+bL4OrCs9KfedvAAAAAAAAAAAhvEavsfmYT+MCp496duDvh7puLyXy7A9AAAAAAAAAAAARLC9ICV8P+juhL0O2H6+CA12vcsSZj0AAAAAAAAAALNmEr164pM/qq7Nvf/VZb55PQq98sK/vAAAAAAAAAAAM4gjPkRCUD/1Dqy990SPvnWydT0AB+29AAAAAAAAAACAPRi9+tOpP5rKK74AwXy+dmS2vSfeyL0AAAAAAAAAAK0sA77LfLM/CbeLvkKkbL6oFTG+MucfvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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,
+    "_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": 248,
+    "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "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,
+    "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 sha256:7108d425c7f2d0ca71189b6bb85cd72cfa8ee7fe747c8e62f5b08a4b1254df91
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ce8da963c621655b88f5b57ab9f7ae9efdb77441075c1669551d7d48dd2f7364
+size 43762

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.3.0+cu121
+- GPU Enabled: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 247.23698660000005, "std_reward": 16.819680184158432, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-07-16T14:35:04.813397"}