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: 278.63 +/- 23.50
+      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 0x7eb70a1a76d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7eb70a1a7760>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7eb70a1a77f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7eb70a1a7880>", "_build": "<function ActorCriticPolicy._build at 0x7eb70a1a7910>", "forward": "<function ActorCriticPolicy.forward at 0x7eb70a1a79a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7eb70a1a7a30>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7eb70a1a7ac0>", "_predict": "<function ActorCriticPolicy._predict at 0x7eb70a1a7b50>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7eb70a1a7be0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7eb70a1a7c70>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7eb70a1a7d00>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7eb70a142340>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1001000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1725708902527653430, "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": -0.014793206793206837, "_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": 496, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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": "2.4.0+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 sha256:6bfb837ccf6929acce3059018edd29ba4505e45abb599d1236ea3a628e5f7e00
+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 0x7eb70a1a76d0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7eb70a1a7760>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7eb70a1a77f0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7eb70a1a7880>",
+        "_build": "<function ActorCriticPolicy._build at 0x7eb70a1a7910>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7eb70a1a79a0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7eb70a1a7a30>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7eb70a1a7ac0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7eb70a1a7b50>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7eb70a1a7be0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7eb70a1a7c70>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7eb70a1a7d00>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7eb70a142340>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1001000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1725708902527653430,
+    "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": -0.014793206793206837,
+    "_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": 496,
+    "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 sha256:5717b06afb9594051c36f4f7f0147b31f2307d3b40c3f1fb3b4e002aa53b5901
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29320c348345227cd768eceb89054dffc3b6bedfbc9ce1d880835317cb56b266
+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: 2.4.0+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": 278.6287818016696, "std_reward": 23.499477764560623, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-09-07T12:07:39.817036"}