Initial commit

.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

@@ -1,3 +1,37 @@
----
-license: mit
----
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: MlpPolicy
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 247.95 +/- 47.46
+      name: mean_reward
+      verified: false
+---
+
+# **MlpPolicy** Agent playing **LunarLander-v2**
+This is a trained model of a **MlpPolicy** 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 0x7c71f491fe20>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c71f491fec0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c71f491ff60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c71f4920040>", "_build": "<function ActorCriticPolicy._build at 0x7c71f49200e0>", "forward": "<function ActorCriticPolicy.forward at 0x7c71f4920180>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c71f4920220>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c71f49202c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c71f4920360>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c71f4920400>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c71f49204a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c71f4920540>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c71f4a86240>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1742907199256034572, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAAA6vkk+rhS3vJP8+Lr+5Vg54Sgnvo5iJDoAAIA/AACAP2B+A765JT4+xIbKPVFXWL4T8Lc882DRugAAAAAAAAAAWvvDvch3vT8OUCe/63ZBPT3zD71SxCO+AAAAAAAAAACA11g9GfOmP/3QIj8y+Cq/7PegvDoDoD0AAAAAAAAAACb+Vj7rhoA9I0wPvgEsOb4aRs26eyfxuwAAAAAAAAAAM7nKvexBmbkIzAs+Dy6Vts+OCDxMbJO1AACAPwAAAABN4Fq+9kyJP2A7Bb/mbSC/cP2jvnaBc74AAAAAAAAAANpcxT2/p6w/iPSbPj36+r6KYH09cvtpPQAAAAAAAAAAM7xGvXpLlT8OiAy+7G8mv1x/Yr3Qofm8AAAAAAAAAADmAHK9iJqGPWLY5z0QYxW+t3FcPZvBlLwAAAAAAAAAACb5Pb5c2ii8/svxOrrG9Th/9509PsjIuQAAgD8AAIA/BlI3PsO6aLzvsxI7/mJYueeFzr1WHy+6AACAPwAAgD9mzCU+pAZJPM6zHbtQU5S5Y27ZPXYnj7oAAIA/AACAP3NQCr40vBs+kYwxO65LNL6tqSG8uJHOPAAAAAAAAAAALchAPq7L2LzmNec7tS2buqIGRr4w2Wi7AACAPwAAgD/zZiO+NtBWvAdturpLQaS4B6C8PWMRADoAAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEEsIhpSMAUOUdJRSlC4="}, "_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": 310, "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": 2048, "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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"}, "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": "2.6.0+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:ae26c09dda08f7602ffed589c0d5ba5b0687f2dfd5326c309475d40eca552493
+size 148046

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 0x7c71f491fe20>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c71f491fec0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c71f491ff60>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c71f4920040>",
+        "_build": "<function ActorCriticPolicy._build at 0x7c71f49200e0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7c71f4920180>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c71f4920220>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c71f49202c0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7c71f4920360>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c71f4920400>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c71f49204a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c71f4920540>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7c71f4a86240>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1742907199256034572,
+    "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": 310,
+    "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": 2048,
+    "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5eb9b011030f68a0546531fd32bb4703684547924060a841b56ee5acdda11955
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37bd889b6c35a368c3a9984465414d3081949d8a40b4521438d502c864177449
+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: 2.6.0+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:f9f5eb0e38a39d5df63fff354e2d9e124a963a7d2657a6413562360023639af7
+size 149389

results.json

@@ -0,0 +1 @@
+{"mean_reward": 247.94878250000002, "std_reward": 47.46329812302868, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-03-25T13:29:46.632694"}