Upload 6 files

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz 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

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: 292.16 +/- 19.84
+      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 0x7b9511f231c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b9511f23250>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b9511f232e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b9511f23370>", "_build": "<function ActorCriticPolicy._build at 0x7b9511f23400>", "forward": "<function ActorCriticPolicy.forward at 0x7b9511f23490>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b9511f23520>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b9511f235b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b9511f23640>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b9511f236d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b9511f23760>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b9511f237f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b95120cad80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711225428487455303, "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": -0.004885333333333408, "_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": 7360, "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": 40, "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-6.1.58+-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": "2.2.1+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 sha256:62b8f00a59ff9d6acf1a296489ea734fced194a49b017a79c5ee6221857977ea
+size 147451

results.json

@@ -0,0 +1 @@
+{"mean_reward": 292.16051978167815, "std_reward": 19.838880452940646, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-23T23:41:34.703561"}