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: 242.22 +/- 21.41
+      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 0x7d8c5ea97d80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d8c5ea97e20>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d8c5ea97ec0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d8c5ea97f60>", "_build": "<function ActorCriticPolicy._build at 0x7d8c5ea9c040>", "forward": "<function ActorCriticPolicy.forward at 0x7d8c5ea9c0e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d8c5ea9c180>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d8c5ea9c220>", "_predict": "<function ActorCriticPolicy._predict at 0x7d8c5ea9c2c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d8c5ea9c360>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d8c5ea9c400>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d8c5ea9c4a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d8c6104ee40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1739392713784433507, "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "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 sha256:81654731ba55adae1570a508897bc731b62eb9e6224e37eee5036964db9f7100
+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 0x7d8c5ea97d80>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d8c5ea97e20>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d8c5ea97ec0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d8c5ea97f60>",
+        "_build": "<function ActorCriticPolicy._build at 0x7d8c5ea9c040>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7d8c5ea9c0e0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d8c5ea9c180>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d8c5ea9c220>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7d8c5ea9c2c0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d8c5ea9c360>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d8c5ea9c400>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d8c5ea9c4a0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7d8c6104ee40>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1739392713784433507,
+    "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 sha256:64adca8f87c3b615ae06ba3be503a2d009e8bfc1b752225126fcc37f46ca3a0c
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:769b8d9455e4e417a9ead895fa059f7b9d9d60bf4f3d7294ac93ce1a78f185cc
+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 sha256:9e2b2c411130beb52d12f5d8f9315f9a9ace80a20ab52b2e3cd4bd80e11441d6
+size 182930

results.json

@@ -0,0 +1 @@
+{"mean_reward": 242.221697, "std_reward": 21.412707553666493, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-02-12T21:04:13.587509"}