Upload my trained agent use PPO for LunarLander-v2

README.md

@@ -1,3 +1,37 @@
----
-license: mit
----
+---
+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: 270.85 +/- 16.91
+      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 0x7fc240e54b80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc240e54c10>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc240e54ca0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc240e54d30>", "_build": "<function ActorCriticPolicy._build at 0x7fc240e54dc0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc240e54e50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc240e54ee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc240e54f70>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc240e55000>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc240e55090>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc240e55120>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc240e551b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fc240df3800>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1212416, "_total_timesteps": 1200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716008220050861700, "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": -0.010346666666666726, "_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": 296, "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 Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+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 sha256:7c4f3c4283f096014ae81ce9c6ea3b44379469e554a6f2ee3b9c38577e0a2455
+size 147529

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 0x7fc240e54b80>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc240e54c10>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc240e54ca0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc240e54d30>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fc240e54dc0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fc240e54e50>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fc240e54ee0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc240e54f70>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fc240e55000>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc240e55090>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc240e55120>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc240e551b0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fc240df3800>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1212416,
+    "_total_timesteps": 1200000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1716008220050861700,
+    "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": -0.010346666666666726,
+    "_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": 296,
+    "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 sha256:51e8b0c2e52842e682cd6d0e019ddf32ad9419366956f19a198611f3271c3ffe
+size 87978

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c341cf89a391edb13d49c58368cdd9d375f5d9c39b31e7d279c91441d20637ee
+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: 2.2.1+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": 270.84962409999997, "std_reward": 16.908814431230528, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-18T05:25:51.339066"}