Upload PPO LunarLander-v2 trained agent

README.md

@@ -1,3 +1,37 @@
 ---
-license: apache-2.0
+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: 236.20 +/- 23.22
+      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 0x7f23111a8f70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f23111a9000>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f23111a9090>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f23111a9120>", "_build": "<function ActorCriticPolicy._build at 0x7f23111a91b0>", "forward": "<function ActorCriticPolicy.forward at 0x7f23111a9240>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f23111a92d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f23111a9360>", "_predict": "<function ActorCriticPolicy._predict at 0x7f23111a93f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f23111a9480>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f23111a9510>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f23111a95a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f23111936c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1683965477505277161, "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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"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.0+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 sha256:8d234735d5426c90b93a0b82b24214d1b55b0be563dd98f2d4448fc27686a12a
+size 146755

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 0x7f23111a8f70>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f23111a9000>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f23111a9090>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f23111a9120>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f23111a91b0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f23111a9240>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f23111a92d0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f23111a9360>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f23111a93f0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f23111a9480>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f23111a9510>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f23111a95a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f23111936c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1683965477505277161,
+    "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:331bbc842d293936e559d8b281248be18c9e9635a5b5bfe15b7fccc5922d87fb
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8a8e2ef3b19a00a90c18118df85ab2b0799baf86ed7fc639442770f11d0c0158
+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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
+- Python: 3.10.11
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.0.0+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": 236.1988532854773, "std_reward": 23.2192219384921, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-13T08:40:39.610328"}