Upload PPO LunarLander-v2 trained agent

.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: 262.42 +/- 19.39
+      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 0x78e8ea6a4860>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78e8ea6a4900>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78e8ea6a49a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78e8ea6a4a40>", "_build": "<function ActorCriticPolicy._build at 0x78e8ea6a4ae0>", "forward": "<function ActorCriticPolicy.forward at 0x78e8ea6a4b80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x78e8ea6a4c20>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78e8ea6a4cc0>", "_predict": "<function ActorCriticPolicy._predict at 0x78e8ea6a4d60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78e8ea6a4e00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78e8ea6a4ea0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x78e8ea6a4f40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78e8ea619380>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1745717706970497954, "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:": "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.12", "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 sha256:445e46ba952f6fcefc04bf792072c2fa30ade8cd8fc9135a3d660ca1f2c83ab9
+size 148132

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 0x78e8ea6a4860>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78e8ea6a4900>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78e8ea6a49a0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78e8ea6a4a40>",
+        "_build": "<function ActorCriticPolicy._build at 0x78e8ea6a4ae0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x78e8ea6a4b80>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x78e8ea6a4c20>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78e8ea6a4cc0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x78e8ea6a4d60>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78e8ea6a4e00>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78e8ea6a4ea0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x78e8ea6a4f40>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x78e8ea619380>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1745717706970497954,
+    "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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc090c1d7a1942454f48a9a938026ecbcc3d7f2d87ce627899382a985a4327ec
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7011f2d2aa8e5486ab239b3da20951bac338a1d864414a2f1198d3c3f30e0c6a
+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: 3.11.12
+- 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:bd4467d4f411c2481b239b73aa609a6c939c2d2e604dcdf7d59067417ec581e7
+size 142966

results.json

@@ -0,0 +1 @@
+{"mean_reward": 262.4206397, "std_reward": 19.3857222001408, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-04-27T02:18:10.427467"}