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: 276.74 +/- 15.72
+      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 0x7ff08281c670>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff08281c700>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff08281c790>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff08281c820>", "_build": "<function ActorCriticPolicy._build at 0x7ff08281c8b0>", "forward": "<function ActorCriticPolicy.forward at 0x7ff08281c940>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff08281c9d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff08281ca60>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff08281caf0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff08281cb80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff08281cc10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff08281cca0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ff0827b9d80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712841571457067373, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAA29gT0fnLu7WQwhvFF6DTzAcw89Nrj5vAAAgD8AAIA/zUAoPXbTuz9F5BI/NciOPsTS7bwGV1u8AAAAAAAAAAAzsYW+W/RiP40o/L0JZZW+as2UvkVFCz0AAAAAAAAAAPrZTD5n674+nXp4voVlhr5zLoi99MwDuwAAAAAAAAAAZgZ4OtxZqD4Fn8G8reGhvvdTZrwaniq9AAAAAAAAAAAArP07HDVEvLZoyrq9TXc95vciO0t34rkAAIA/AACAP4BmDL435wE/Cn6DPjG0zL5rYDI9d4QhvQAAAAAAAAAAsxV5vta3gD8CKps94wi7vtBC3b4isyQ+AAAAAAAAAAAzLrW9NkSRP14xWr5NII++FPJOvvBJMr4AAAAAAAAAAACA4rz0zEo+W/KsPRtTjb6J6GI9mKpJvQAAAAAAAAAA8xaivesMdj8xhx69mmOpvpW0Fb5rL9s9AAAAAAAAAADN3969Jn1/P9wcCr7X+q6+4n8ovc0UMz0AAAAAAAAAAAC06rzDMVu6A6PRt+BOFbnzKI+4kqK9NwAAgD8AAIA/wPPWvVwzUbpzOHs7uTGkOMERqTn7lhi6AACAPwAAAADmwlY99kQQuvLOxzoaQqs0laPeOpok6bkAAIA/AAAAANpEgD1IP6K6whxKucQN4rOxkb+5qy9nOAAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": 280, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+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 sha256:37848a6188e0af25bbf81d610f012b5b0a0d42c496291e0433f071edf606077b
+size 148076

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 0x7ff08281c670>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff08281c700>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff08281c790>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff08281c820>",
+        "_build": "<function ActorCriticPolicy._build at 0x7ff08281c8b0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7ff08281c940>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ff08281c9d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff08281ca60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7ff08281caf0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff08281cb80>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff08281cc10>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff08281cca0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7ff0827b9d80>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1712841571457067373,
+    "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": 280,
+    "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 sha256:07fa6b31c0a3be2598dc18c02e293028a6c4d2b178a73348926fae0118a4b784
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cea6cdac3d217bbb501d0704303a47e2cd680dd1e31275603d0d318129f34104
+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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.2.1+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": 276.74078609529136, "std_reward": 15.720466731569768, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-11T13:43:10.095718"}