Upload PPO LunarLander-v2 trained agent V2

.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: 264.86 +/- 19.94
+      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 0x7d454a8e67a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d454a8e6840>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d454a8e68e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d454a8e6980>", "_build": "<function ActorCriticPolicy._build at 0x7d454a8e6a20>", "forward": "<function ActorCriticPolicy.forward at 0x7d454a8e6ac0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d454a8e6b60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d454a8e6c00>", "_predict": "<function ActorCriticPolicy._predict at 0x7d454a8e6ca0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d454a8e6d40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d454a8e6de0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d454a8e6e80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d454a824d00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1212416, "_total_timesteps": 1200000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1738761040495914234, "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": -0.010346666666666726, "_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": 592, "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": 8, "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-6.1.85+-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 sha256:3017e621a27b06cd88547e73c64d13bcc5d2babfa72951492e608a69d78edb72
+size 148064

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 0x7d454a8e67a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d454a8e6840>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d454a8e68e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d454a8e6980>",
+        "_build": "<function ActorCriticPolicy._build at 0x7d454a8e6a20>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7d454a8e6ac0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d454a8e6b60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d454a8e6c00>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7d454a8e6ca0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d454a8e6d40>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d454a8e6de0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d454a8e6e80>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7d454a824d00>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1212416,
+    "_total_timesteps": 1200000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1738761040495914234,
+    "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": -0.010346666666666726,
+    "_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": 592,
+    "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": 8,
+    "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 sha256:6f859a874c066268d46ac5e80ebea5bd582b32bcff87e18651c30e73e1f66580
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3eb49435e16c5c8c0dc185c239ba85ffd95d05e8016e6d8937b3765ee80172d4
+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 sha256:3d0a733fe0f137c89a836a110ba725119a9d45496b14208ac5b0fbc69b432748
+size 179121

results.json

@@ -0,0 +1 @@
+{"mean_reward": 264.8649101, "std_reward": 19.937193690540507, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-02-05T13:40:42.145602"}