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: 241.70 +/- 16.36
+      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 0x7c399f10b370>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c399f10b400>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c399f10b490>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c399f10b520>", "_build": "<function ActorCriticPolicy._build at 0x7c399f10b5b0>", "forward": "<function ActorCriticPolicy.forward at 0x7c399f10b640>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c399f10b6d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c399f10b760>", "_predict": "<function ActorCriticPolicy._predict at 0x7c399f10b7f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c399f10b880>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c399f10b910>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c399f10b9a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c39bd6aba00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718693448279382730, "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:": "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "False", "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:a126b8d4caab25bc9fe60a2bd390a69e5ca7e0e74045b1cea704c82dd96d95e0
+size 147573

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 0x7c399f10b370>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c399f10b400>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c399f10b490>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c399f10b520>",
+        "_build": "<function ActorCriticPolicy._build at 0x7c399f10b5b0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7c399f10b640>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c399f10b6d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c399f10b760>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7c399f10b7f0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c399f10b880>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c399f10b910>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c399f10b9a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7c39bd6aba00>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1718693448279382730,
+    "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:": "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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:c8d30e6bffc4b91f57ce9282d526ed5633f69682b56a0419de239b479ecea443
+size 87978

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e155c2867af9d2fc437bd48f1205f8f04c38343472793d159b3274285a5b920c
+size 43634

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 Sun Apr 28 14:29:16 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.3.0+cu121
+- GPU Enabled: False
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 241.70001634780073, "std_reward": 16.35843973682067, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-18T07:29:42.494962"}