My first one

.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: 257.10 +/- 22.89
+      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 0x7db52c76fc40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7db52c76fce0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7db52c76fd80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7db52c76fe20>", "_build": "<function ActorCriticPolicy._build at 0x7db52c76fec0>", "forward": "<function ActorCriticPolicy.forward at 0x7db52c76ff60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7db52c778040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7db52c7780e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7db52c778180>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7db52c778220>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7db52c7782c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7db52c778360>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7db52eacf940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1752895863876840805, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "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:ebe3f3ba7760c1020eaf720695dfdf803f2438a3efbe0d2fb257a3c1c91664a3
+size 148124

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 0x7db52c76fc40>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7db52c76fce0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7db52c76fd80>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7db52c76fe20>",
+        "_build": "<function ActorCriticPolicy._build at 0x7db52c76fec0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7db52c76ff60>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7db52c778040>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7db52c7780e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7db52c778180>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7db52c778220>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7db52c7782c0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7db52c778360>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7db52eacf940>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1752895863876840805,
+    "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
+    },
+    "_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:": "gAWVdwIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBNudW1weS5fY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolggAAAAAAAAAAQEBAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBEolggAAAAAAAAAAQEBAQEBAQGUaBVLCIWUaBl0lFKUjAZfc2hhcGWUSwiFlIwDbG93lGgRKJYgAAAAAAAAAAAAtMIAALTCAACgwAAAoMDbD0nAAACgwAAAAIAAAACAlGgLSwiFlGgZdJRSlIwEaGlnaJRoESiWIAAAAAAAAAAAALRCAAC0QgAAoEAAAKBA2w9JQAAAoEAAAIA/AACAP5RoC0sIhZRoGXSUUpSMCGxvd19yZXBylIxbWy05MC4gICAgICAgIC05MC4gICAgICAgICAtNS4gICAgICAgICAtNS4gICAgICAgICAtMy4xNDE1OTI3ICAtNS4KICAtMC4gICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMU1s5MC4gICAgICAgIDkwLiAgICAgICAgIDUuICAgICAgICAgNS4gICAgICAgICAzLjE0MTU5MjcgIDUuCiAgMS4gICAgICAgICAxLiAgICAgICBdlIwKX25wX3JhbmRvbZROdWIu",
+        "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
+        "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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:256f9e0a0aeec412fa5a02a39667fe3ebe2c010def5a5e944b5e3e64fa77f304
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a050a8ec3f620cd62a18cc00eaf1dce499ec3556aa50296aa0726afa10b714c0
+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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
+- Python: 3.11.13
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.6.0+cu124
+- GPU Enabled: True
+- Numpy: 2.0.2
+- 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 sha256:3b292627c29ab518577e20a28d32b1e3c254f54e8d5d99e9b62f69ca0b8b2a26
+size 161236

results.json

@@ -0,0 +1 @@
+{"mean_reward": 257.0957476, "std_reward": 22.890745722436883, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-07-19T03:56:38.793264"}