First RL 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: 264.55 +/- 21.90
+      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 0x7f912fd8d870>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f912fd8d900>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f912fd8d990>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f912fd8da20>", "_build": "<function ActorCriticPolicy._build at 0x7f912fd8dab0>", "forward": "<function ActorCriticPolicy.forward at 0x7f912fd8db40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f912fd8dbd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f912fd8dc60>", "_predict": "<function ActorCriticPolicy._predict at 0x7f912fd8dcf0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f912fd8dd80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f912fd8de10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f912fd8dea0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f9149968600>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1683222641816616649, "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": 310, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "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:b394407fb547197b20bd790c9c8731a012a2426768e82d5629b4ffce256a1219
+size 146662

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 0x7f912fd8d870>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f912fd8d900>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f912fd8d990>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f912fd8da20>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f912fd8dab0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f912fd8db40>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f912fd8dbd0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f912fd8dc60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f912fd8dcf0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f912fd8dd80>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f912fd8de10>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f912fd8dea0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f9149968600>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1683222641816616649,
+    "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": 310,
+    "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "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 sha256:8d48cbb718dc059c82f78eb818ea14453b8fee3c7f218f53003c8085632d28ba
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:03e86bd1bbbd33626d1d3ec60e046d4f673e92d78be72aa8504c87536692c32c
+size 43329

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
+- Python: 3.10.11
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.0.0+cu118
+- GPU Enabled: True
+- Numpy: 1.22.4
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 264.5466720494483, "std_reward": 21.90464609269852, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-04T18:22:48.456069"}