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: 252.37 +/- 17.54
+      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 0x79a7ef1b55a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79a7ef1b5630>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79a7ef1b56c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79a7ef1b5750>", "_build": "<function ActorCriticPolicy._build at 0x79a7ef1b57e0>", "forward": "<function ActorCriticPolicy.forward at 0x79a7ef1b5870>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79a7ef1b5900>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79a7ef1b5990>", "_predict": "<function ActorCriticPolicy._predict at 0x79a7ef1b5a20>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79a7ef1b5ab0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79a7ef1b5b40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79a7ef1b5bd0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79a7ef1a7940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1690762397086788992, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAACgwDvhpJq6mCFmuhXCXbWia086rK6EOQAAgD8AAIA/ZhC6PPYcGrqgg3I6TAy2NWL15TixJ4+5AACAPwAAgD/N6E4+2ZYcPsPrKL4i8HS+OBJVuV/PKr0AAAAAAAAAAGb8XT3hCJe6ws7wt+1kCLZSb+O5EgkPNwAAgD8AAIA/AKsIveFYm7orpZG64gCTtUQyQTr4Dqg5AACAPwAAgD/AV4Q9j4Ihuvpm87lA/YmzDnmiO7pzwbEAAIA/AACAP806bj3hkJO62mQGuisW7rOheo+6W7QbOQAAgD8AAIA/AP9ePcOdf7o9OOk6zXBDNBadbrvtxwa6AACAPwAAgD8AaBG79qxEuqss57UcEhKxIWRyOpwDFDUAAIA/AACAP2YF1bw0XM4+A5nQPeQRV76Ts7A96L9pPQAAAAAAAAAAZqrqO4UDt7kaRqK6Qa2LNGdLnLqT9/SzAACAPwAAgD+zA2g94TqSujCtz7zDHSw1HCcIuzNDnbQAAIA/AACAP2ablz3DvWW64Dpou0d4HjiJ9O+6MpALOgAAgD8AAIA/5mhuPa5NqLpma1C55GpBtGXapLrWXm84AACAPwAAgD9mVkw9FAyhut5kULu6f4U4nrpQufgYRjkAAIA/AACAP2ByUT5X3Fo/C1tpPdiZgL4cZQw+prPDPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": 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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.6", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "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 sha256:1656af4582572899b550ba3cb8b7406aed38a2b9cb390fd8c83406de60395b6b
+size 146753

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 0x79a7ef1b55a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79a7ef1b5630>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79a7ef1b56c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79a7ef1b5750>",
+        "_build": "<function ActorCriticPolicy._build at 0x79a7ef1b57e0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x79a7ef1b5870>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x79a7ef1b5900>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79a7ef1b5990>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x79a7ef1b5a20>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79a7ef1b5ab0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79a7ef1b5b40>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x79a7ef1b5bd0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x79a7ef1a7940>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1690762397086788992,
+    "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "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 sha256:11c319f70975e75c590ec986e392125bd6f71fe008306836b9fec55ec4ab8e4b
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7b1dee6431ad871afb507d4974580cafead5b347a25a31ad8c418afcfa05c2ab
+size 43329

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
+- Python: 3.10.6
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.0.1+cu118
+- GPU Enabled: True
+- Numpy: 1.22.4
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 252.3656474, "std_reward": 17.54452926402876, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-31T00:44:30.323288"}