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: 264.74 +/- 16.38
+      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 0x7cd35581c8b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cd35581c940>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cd35581c9d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cd35581ca60>", "_build": "<function ActorCriticPolicy._build at 0x7cd35581caf0>", "forward": "<function ActorCriticPolicy.forward at 0x7cd35581cb80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cd35581cc10>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cd35581cca0>", "_predict": "<function ActorCriticPolicy._predict at 0x7cd35581cd30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cd35581cdc0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cd35581ce50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cd35581cee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cd35830b6c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1733144104515432158, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAEAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+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": "2.5.1+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:a3c7eab00257033c0c22e6c52a9d65ba02c7ae778260280d5549b4a07518bf5f
+size 148008

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 0x7cd35581c8b0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7cd35581c940>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7cd35581c9d0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7cd35581ca60>",
+        "_build": "<function ActorCriticPolicy._build at 0x7cd35581caf0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7cd35581cb80>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7cd35581cc10>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7cd35581cca0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7cd35581cd30>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7cd35581cdc0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7cd35581ce50>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7cd35581cee0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7cd35830b6c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1733144104515432158,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAEAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+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:f1d1824db61cfd983d08f7894181d1d87e1c6f88a4e00da20c214055353b6de4
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9d35b9c30abf476822dfe3c9396ce0403bac181204689daf3486120c1b0ca831
+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": 264.73630131573464, "std_reward": 16.381270255632035, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-12-02T13:21:33.543105"}