Upload PPO LunarLander-v2 trained agent commit 3

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: 288.99 +/- 15.88
+      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 0x78fbc0e296c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78fbc0e29750>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78fbc0e297e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78fbc0e29870>", "_build": "<function ActorCriticPolicy._build at 0x78fbc0e29900>", "forward": "<function ActorCriticPolicy.forward at 0x78fbc0e29990>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78fbc0e29a20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78fbc0e29ab0>", "_predict": "<function ActorCriticPolicy._predict at 0x78fbc0e29b40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78fbc0e29bd0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78fbc0e29c60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78fbc0e29cf0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78fbc1cdcb40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 10010624, "_total_timesteps": 10000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716653772774666748, "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": -0.0010623999999999079, "_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": 2692, "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 Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "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:a7650eb08bd3caf2bde5b15df14c9edfb4e356bedd2cc040bb24b159a4e02935
+size 147956

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 0x78fbc0e296c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78fbc0e29750>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78fbc0e297e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78fbc0e29870>",
+        "_build": "<function ActorCriticPolicy._build at 0x78fbc0e29900>",
+        "forward": "<function ActorCriticPolicy.forward at 0x78fbc0e29990>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x78fbc0e29a20>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78fbc0e29ab0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x78fbc0e29b40>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78fbc0e29bd0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78fbc0e29c60>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x78fbc0e29cf0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x78fbc1cdcb40>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 10010624,
+    "_total_timesteps": 10000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1716653772774666748,
+    "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": -0.0010623999999999079,
+    "_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": 2692,
+    "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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4eea825dcaf180336269b153fefc1467e15d8c60de2700e241c86d65df28159a
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7b2f2c232fe1d75f693899c7a5556a80db741f990756f49b0aa88c4e8192dee9
+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 Sun Apr 28 14:29:16 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.3.0+cu121
+- GPU Enabled: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 288.9918471149023, "std_reward": 15.876164525561903, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-25T18:39:19.801734"}