First commit of trained model

.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: 260.63 +/- 9.22
+      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 0x7db5db668400>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7db5db6684a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7db5db668540>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7db5db6685e0>", "_build": "<function ActorCriticPolicy._build at 0x7db5db668680>", "forward": "<function ActorCriticPolicy.forward at 0x7db5db668720>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7db5db6687c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7db5db668860>", "_predict": "<function ActorCriticPolicy._predict at 0x7db5db668900>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7db5db6689a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7db5db668a40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7db5db668ae0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7db5db765100>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1741796527383931037, "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:": "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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 sha256:66b647ba56691cc94563757191476801861623a695796a57796f3927ec4821d8
+size 148130

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 0x7db5db668400>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7db5db6684a0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7db5db668540>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7db5db6685e0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7db5db668680>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7db5db668720>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7db5db6687c0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7db5db668860>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7db5db668900>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7db5db6689a0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7db5db668a40>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7db5db668ae0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7db5db765100>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000.0,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1741796527383931037,
+    "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:": "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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6fc80623934e07794cfb49c2c55e4f0c2ebdba6b238a33ae6aa9bf4f1ef3e432
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ddbdffa43ff44863ee170449921f9659bdc76a1d80266fe66692ec0305f1a201
+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 sha256:281a8b546bbbc552e5e2518d911a672631c4a8fde0a0d66591f5fa8cbc5a05db
+size 191924

results.json

@@ -0,0 +1 @@
+{"mean_reward": 260.63090109999996, "std_reward": 9.220524008417218, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-03-12T16:49:24.004030"}