Upload PPO BipedalWalker-v3 trained agent

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- BipedalWalker-v3
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: BipedalWalker-v3
+      type: BipedalWalker-v3
+    metrics:
+    - type: mean_reward
+      value: -74.70 +/- 17.91
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **BipedalWalker-v3**
+This is a trained model of a **PPO** agent playing **BipedalWalker-v3**
+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 0x7e717ff875b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e717ff87640>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e717ff876d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e717ff87760>", "_build": "<function ActorCriticPolicy._build at 0x7e717ff877f0>", "forward": "<function ActorCriticPolicy.forward at 0x7e717ff87880>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e717ff87910>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e717ff879a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e717ff87a30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e717ff87ac0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e717ff87b50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e717ff87be0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e71817b0b80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1713002287743775218, "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  True  True  True  True\n  True  True  True  True  True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True  True  True  True  True\n  True  True  True  True  True  True  True  True  True  True  True  True]", "_shape": [24], "low": "[-3.1415927 -5.        -5.        -5.        -3.1415927 -5.\n -3.1415927 -5.        -0.        -3.1415927 -5.        -3.1415927\n -5.        -0.        -1.        -1.        -1.        -1.\n -1.        -1.        -1.        -1.        -1.        -1.       ]", "high": "[3.1415927 5.        5.        5.        3.1415927 5.        3.1415927\n 5.        5.        3.1415927 5.        3.1415927 5.        5.\n 1.        1.        1.        1.        1.        1.        1.\n 1.        1.        1.       ]", "low_repr": "[-3.1415927 -5.        -5.        -5.        -3.1415927 -5.\n -3.1415927 -5.        -0.        -3.1415927 -5.        -3.1415927\n -5.        -0.        -1.        -1.        -1.        -1.\n -1.        -1.        -1.        -1.        -1.        -1.       ]", "high_repr": "[3.1415927 5.        5.        5.        3.1415927 5.        3.1415927\n 5.        5.        3.1415927 5.        3.1415927 5.        5.\n 1.        1.        1.        1.        1.        1.        1.\n 1.        1.        1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True]", "bounded_above": "[ True  True  True  True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-Bipedalwalker-v3.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:24bb187e0f179e878291993fc8aea7d33b39aa79a2c11d5b6ebdf307a33b1d1f
+size 176961

ppo-Bipedalwalker-v3/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-Bipedalwalker-v3/data

@@ -0,0 +1,105 @@
+{
+    "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 0x7e717ff875b0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e717ff87640>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e717ff876d0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e717ff87760>",
+        "_build": "<function ActorCriticPolicy._build at 0x7e717ff877f0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7e717ff87880>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e717ff87910>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e717ff879a0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7e717ff87a30>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e717ff87ac0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e717ff87b50>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e717ff87be0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7e71817b0b80>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1713002287743775218,
+    "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  True  True  True  True\n  True  True  True  True  True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True  True  True  True  True\n  True  True  True  True  True  True  True  True  True  True  True  True]",
+        "_shape": [
+            24
+        ],
+        "low": "[-3.1415927 -5.        -5.        -5.        -3.1415927 -5.\n -3.1415927 -5.        -0.        -3.1415927 -5.        -3.1415927\n -5.        -0.        -1.        -1.        -1.        -1.\n -1.        -1.        -1.        -1.        -1.        -1.       ]",
+        "high": "[3.1415927 5.        5.        5.        3.1415927 5.        3.1415927\n 5.        5.        3.1415927 5.        3.1415927 5.        5.\n 1.        1.        1.        1.        1.        1.        1.\n 1.        1.        1.       ]",
+        "low_repr": "[-3.1415927 -5.        -5.        -5.        -3.1415927 -5.\n -3.1415927 -5.        -0.        -3.1415927 -5.        -3.1415927\n -5.        -0.        -1.        -1.        -1.        -1.\n -1.        -1.        -1.        -1.        -1.        -1.       ]",
+        "high_repr": "[3.1415927 5.        5.        5.        3.1415927 5.        3.1415927\n 5.        5.        3.1415927 5.        3.1415927 5.        5.\n 1.        1.        1.        1.        1.        1.        1.\n 1.        1.        1.       ]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True]",
+        "bounded_above": "[ True  True  True  True]",
+        "_shape": [
+            4
+        ],
+        "low": "[-1. -1. -1. -1.]",
+        "high": "[1. 1. 1. 1.]",
+        "low_repr": "-1.0",
+        "high_repr": "1.0",
+        "_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-Bipedalwalker-v3/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:58d155aa748f1474d73404d3f90f6b0ede334134275002f94a76e89bfa253e0b
+size 105441

ppo-Bipedalwalker-v3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6f904b5db4d1d94b3dd029b99960bc0fedea809b9c789819806dc2ad464f084b
+size 52271

ppo-Bipedalwalker-v3/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-Bipedalwalker-v3/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.2.1+cu121
+- GPU Enabled: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": -74.6996438138547, "std_reward": 17.910507130441367, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-13T10:56:19.364688"}