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: 257.69 +/- 22.86
+      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 0x7bd762944e50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bd762944ee0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bd762944f70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bd762945000>", "_build": "<function ActorCriticPolicy._build at 0x7bd762945090>", "forward": "<function ActorCriticPolicy.forward at 0x7bd762945120>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bd7629451b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bd762945240>", "_predict": "<function ActorCriticPolicy._predict at 0x7bd7629452d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bd762945360>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bd7629453f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bd762945480>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bd7628e3540>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708617221754973069, "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:": "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "False", "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 sha256:3d7acc0db9c442d5418599b3aef29c77295c635bb2c0139a9d771dde0e90636d
+size 147565

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 0x7bd762944e50>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bd762944ee0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bd762944f70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bd762945000>",
+        "_build": "<function ActorCriticPolicy._build at 0x7bd762945090>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7bd762945120>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bd7629451b0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bd762945240>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7bd7629452d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bd762945360>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bd7629453f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bd762945480>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7bd7628e3540>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1708617221754973069,
+    "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:": "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 sha256:9c8fd3b4767fe39cd27acca4271a4f4dc8b7bb95f9fb7a95e04ec28f28483a7c
+size 87978

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ed0c38951797f9ab5fe69916e68e876ceabfa59e64e4a258d87b7b2a90d8cba6
+size 43634

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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.1.0+cu121
+- GPU Enabled: False
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 257.68599896445596, "std_reward": 22.856763577259997, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-22T16:40:49.750700"}