init

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

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: 247.22 +/- 28.67
+      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 0x7bd04a02d1c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bd04a02d260>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bd04a02d300>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bd04a02d3a0>", "_build": "<function ActorCriticPolicy._build at 0x7bd04a02d440>", "forward": "<function ActorCriticPolicy.forward at 0x7bd04a02d4e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bd04a02d580>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bd04a02d620>", "_predict": "<function ActorCriticPolicy._predict at 0x7bd04a02d6c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bd04a02d760>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bd04a02d800>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bd04a02d8a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bd04a1746c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1741922200047476086, "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": 1092, "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": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "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": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "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 sha256:2eda461f910987ec6d0aa9241d64ed1fa1da59203220240b77a78f524d3ae86f
+size 148054

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 0x7bd04a02d1c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bd04a02d260>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bd04a02d300>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bd04a02d3a0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7bd04a02d440>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7bd04a02d4e0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bd04a02d580>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bd04a02d620>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7bd04a02d6c0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bd04a02d760>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bd04a02d800>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bd04a02d8a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7bd04a1746c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000.0,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1741922200047476086,
+    "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": 1092,
+    "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": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "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 sha256:7b877849e163533b822acb4fe5d056f951fe3db2f89022369cd63001b05bc02a
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d4818bbf6538c522c1f0847d3b8299b9c97fc1d52167fdc79b5cdf961495ace4
+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: 3.11.11
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.5.1+cu124
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e32485d312b62ba8e279167754dd867f1e76e7f7e16b7e5c7fccf0920b403f42
+size 189848

results.json

@@ -0,0 +1 @@
+{"mean_reward": 247.21667229999997, "std_reward": 28.673238447860268, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-03-14T03:38:31.163604"}