Upload PPO LunarLander-v2 trained agent

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: 210.73 +/- 77.64
+      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 0x7c79ad44d000>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c79ad44d090>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c79ad44d120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c79ad44d1b0>", "_build": "<function ActorCriticPolicy._build at 0x7c79ad44d240>", "forward": "<function ActorCriticPolicy.forward at 0x7c79ad44d2d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c79ad44d360>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c79ad44d3f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c79ad44d480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c79ad44d510>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c79ad44d5a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c79ad44d630>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c79bae09d40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1725814826201483370, "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": 252, "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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"}, "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": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.4.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "2.2.1", "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 sha256:384fe2a14590898afbbf6ff01e5ffe2d5e96ff21e2c6283a68a69f9e12d1afe7
+size 148084

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 0x7c79ad44d000>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c79ad44d090>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c79ad44d120>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c79ad44d1b0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7c79ad44d240>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7c79ad44d2d0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c79ad44d360>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c79ad44d3f0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7c79ad44d480>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c79ad44d510>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c79ad44d5a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c79ad44d630>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7c79bae09d40>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1725814826201483370,
+    "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": 252,
+    "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 sha256:78dc40cdbd4ded05265d9225bfd73b0960b55a9b1c9b5071b191e5b967b2dfa6
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ce745f33a938274ffaa4828326e1b4e8b62d6a42d212c3529140b4d9a02b9eb0
+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: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.4.0+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 210.72687331430498, "std_reward": 77.63651954540022, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-09-08T17:24:46.187522"}