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: 273.10 +/- 20.91
+      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 0x7949a1083010>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7949a10830a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7949a1083130>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7949a10831c0>", "_build": "<function ActorCriticPolicy._build at 0x7949a1083250>", "forward": "<function ActorCriticPolicy.forward at 0x7949a10832e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7949a1083370>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7949a1083400>", "_predict": "<function ActorCriticPolicy._predict at 0x7949a1083490>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7949a1083520>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7949a10835b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7949a1083640>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7949a9618840>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1733466675617002870, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAM21RL0PI0g90ENFPWE1h75v+BS+1extPQAAAAAAAAAAjajpPae15z5sRwK++4KxvoHZV7z0Jr48AAAAAAAAAACaVPK88vLSPrZpAz5vurS+lo3oPL3EpT0AAAAAAAAAAI1Dmj39hXY/WRQPPkAKCb9bwc099fENPAAAAAAAAAAAzapkvJy5JLx26Z869Y2rPJQQhr1S1ow9AACAPwAAgD8zJT+89lxquoYpMTqZk9g1zsKCubaHTrkAAIA/AACAP81mlL3XB5I/hqZUvnwu7L402SW+3Y0TvgAAAAAAAAAAGi5ivTYKZz85nYy9UAXTvvNMHr7W2VM9AAAAAAAAAAAzC328FDuxvLqRCzwluQ89ZoG4vRcaR70AAIA/AACAP0CF5D3cq1M+LdcDvTLTNL4L4C88/tvnOwAAAAAAAAAATZEaPa5dobpR1xa6ZpGBs82erzrFpC05AACAPwAAgD8z+QU8jx5/uurYe7t5lI05ktGzOusB9TkAAIA/AACAPwBgBzoK3is8EuC2PU6tRL4Vh1Y9CpvvvQAAAAAAAAAAhgaWPob6gT/iwhA/mps1v3V/9j4WfIY9AAAAAAAAAAD6Dpe+ja+pPwEbCr/GS+e+0KPmvopxBr4AAAAAAAAAAGavtT1bn6c+qLwhvPCpor6fOQC9stDQPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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:": "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 sha256:9c90606261db047a68cca16a31e77a0c586d52114816f1668401605b6792d178
+size 147972

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 0x7949a1083010>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7949a10830a0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7949a1083130>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7949a10831c0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7949a1083250>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7949a10832e0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7949a1083370>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7949a1083400>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7949a1083490>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7949a1083520>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7949a10835b0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7949a1083640>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7949a9618840>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1733466675617002870,
+    "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 sha256:6098a2b41201e5ac0b0bac6634b579823983de70582d0356dc55059882ba1be0
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f1b6eac15f40d152661c19684db502d7a85b48614318fa33435c55a4c4dfb94b
+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": 273.10019489999996, "std_reward": 20.90922310192565, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-12-06T07:04:29.830110"}