Upload Record Video Test

.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: -57.79 +/- 48.34
+      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 0x7801b0b1aca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7801b0b1ad40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7801b0b1ade0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7801b0b1ae80>", "_build": "<function ActorCriticPolicy._build at 0x7801b0b1af20>", "forward": "<function ActorCriticPolicy.forward at 0x7801b0b1afc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7801b0b1b060>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7801b0b1b100>", "_predict": "<function ActorCriticPolicy._predict at 0x7801b0b1b1a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7801b0b1b240>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7801b0b1b2e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7801b0b1b380>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7801b0c95940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 32768, "_total_timesteps": 1000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1741482601089165096, "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": -31.768, "_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": 10, "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": 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": "2.5.1+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 sha256:5b7c70ebd89451ed0f080abac211f3c03290f174ed22f0cd97089909764175ef
+size 147979

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 0x7801b0b1aca0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7801b0b1ad40>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7801b0b1ade0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7801b0b1ae80>",
+        "_build": "<function ActorCriticPolicy._build at 0x7801b0b1af20>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7801b0b1afc0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7801b0b1b060>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7801b0b1b100>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7801b0b1b1a0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7801b0b1b240>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7801b0b1b2e0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7801b0b1b380>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7801b0c95940>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 32768,
+    "_total_timesteps": 1000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1741482601089165096,
+    "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": -31.768,
+    "_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": 10,
+    "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": 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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ff86b7e5dc5efbfe3ceb07511cb4f2e003c1605bc640b93e755eebb4e5b74722
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:55ec852733315fb0be70e8d2607ce77e3197bce9dc890f0c276571fd7a93833a
+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 sha256:35f60dbe57f57bbb2338c8a14bef96fc918d9741ee23a88b18b93cd62d9f40c5
+size 204832

results.json

@@ -0,0 +1 @@
+{"mean_reward": -57.7923167, "std_reward": 48.34021013468113, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-03-09T01:12:55.220561"}