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: 267.63 +/- 22.35
+      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 0x78aca0b76830>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78aca0b768c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78aca0b76950>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78aca0b769e0>", "_build": "<function ActorCriticPolicy._build at 0x78aca0b76a70>", "forward": "<function ActorCriticPolicy.forward at 0x78aca0b76b00>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78aca0b76b90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78aca0b76c20>", "_predict": "<function ActorCriticPolicy._predict at 0x78aca0b76cb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78aca0b76d40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78aca0b76dd0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78aca0b76e60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78ac43a97980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1735804461218115499, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAQAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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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"}, "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": "2.5.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "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 sha256:02318f4b0da1c21a7e484725776ae3727c46c75f6cae287964dc009b005ed265
+size 147976

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 0x78aca0b76830>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78aca0b768c0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78aca0b76950>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78aca0b769e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x78aca0b76a70>",
+        "forward": "<function ActorCriticPolicy.forward at 0x78aca0b76b00>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x78aca0b76b90>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78aca0b76c20>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x78aca0b76cb0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78aca0b76d40>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78aca0b76dd0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x78aca0b76e60>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x78ac43a97980>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1735804461218115499,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAQAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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:ce46d5069fc86b20c3f0b74a32a788a5558ab680d4b0cea21508f35d2e1ae90e
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d26cfb1a235aa58b32bdc956b363e5215259b06debd920810922f963e72095aa
+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: 2.5.1+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.0
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 267.6339303701502, "std_reward": 22.347369556326605, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-01-02T08:25:23.394506"}