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: 233.68 +/- 38.51
+      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 0x7f15f58c5f30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f15f58c5fc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f15f58c6050>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f15f58c60e0>", "_build": "<function ActorCriticPolicy._build at 0x7f15f58c6170>", "forward": "<function ActorCriticPolicy.forward at 0x7f15f58c6200>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f15f58c6290>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f15f58c6320>", "_predict": "<function ActorCriticPolicy._predict at 0x7f15f58c63b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f15f58c6440>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f15f58c64d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f15f58c6560>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f15f5a68d40>"}, "verbose": 0, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": 123456, "action_noise": null, "start_time": 1723302314568566763, "learning_rate": 0.0001, "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": 310, "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:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 32, "n_epochs": 10, "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": "2.3.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "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 sha256:22f92d05ad7fa1300365bd90dc65eb9d73e3bc209a6e7cc0fe7977ef954ffcc2
+size 148319

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 0x7f15f58c5f30>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f15f58c5fc0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f15f58c6050>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f15f58c60e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f15f58c6170>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f15f58c6200>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f15f58c6290>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f15f58c6320>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f15f58c63b0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f15f58c6440>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f15f58c64d0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f15f58c6560>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f15f5a68d40>"
+    },
+    "verbose": 0,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": 123456,
+    "action_noise": null,
+    "start_time": 1723302314568566763,
+    "learning_rate": 0.0001,
+    "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": 310,
+    "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:": "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",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": "Generator(PCG64)"
+    },
+    "n_envs": 16,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 32,
+    "n_epochs": 10,
+    "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 sha256:4445ecdf895361c3ea62eea991566d6e3465014611a2e827e7c4956d46357938
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:faa4fc78384bcd022c9805a380a758be62fadf8e05233586c2206ff74f81b4e7
+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: 2.3.1+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 233.67559650000004, "std_reward": 38.51183156030254, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-08-10T15:48:41.801088"}