first commit

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: 265.96 +/- 19.29
+      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 0x7f06bbf0a320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f06bbf0a3b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f06bbf0a440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f06bbf0a4d0>", "_build": "<function ActorCriticPolicy._build at 0x7f06bbf0a560>", "forward": "<function ActorCriticPolicy.forward at 0x7f06bbf0a5f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f06bbf0a680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f06bbf0a710>", "_predict": "<function ActorCriticPolicy._predict at 0x7f06bbf0a7a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f06bbf0a830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f06bbf0a8c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f06bbf0a950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f06bbeb53c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 278224, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1723773184062253125, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADOJE71ci1a6VuQyupXTFLbJMoM6rt6JNQAAgD8AAIA/TfQDPfbEI7qqEJs7AM8pNm+Vyzrcgri6AACAPwAAgD8zhKu89igIunvN37sKZyE4oZMRu60rprUAAIA/AACAPxrAGr3D0S26pexZtrSj37G+hZA7d86CNQAAgD8AAIA/5pCOPeK1AD7+oYy+8lJDvgql0b3gqK07AAAAAAAAAADNUbQ8e1KBul0bObl88A+0sWkNOsakVDgAAIA/AACAP4AK0L24nqe5jricO1a2GDg3ahe7ed08twAAgD8AAIA/mpENPKscwT0KVqu9Lo4Jvm7t2jzQFcu8AAAAAAAAAAD6eaU+2xpuPy469D2NIOy+K1mqPkFxL70AAAAAAAAAALPCRL0p6HC6MwfwuAEQpbZHP1Q7nfIVNgAAgD8AAIA/M/HYvOEIiLqt0U47RhQ8OIVyubjlPv65AACAPwAAgD/aD4u99nBxuiWpRrMM4ZUviDbsOiUZzDMAAIA/AACAP2ZC3rspwFa6ZmhhurccRrUv18K6ZMWEOQAAgD8AAIA/5s0ivfbwJLrjpIg5FWEENGEI/DopGqC4AACAPwAAgD+ar8E8NFnvPWXwb75CK4C+k92avR7HPL0AAAAAAAAAAACaeDxIn5C6aDugOlEhgTWRyQq6d3O5uQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": 0.7378560000000001, "_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": 312, "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": "2.3.1+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:b9ed23bc6073f7afd3084c97eaec2236b1c59ef8a2ea1c55ea0799d83708bb88
+size 148080

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 0x7f06bbf0a320>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f06bbf0a3b0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f06bbf0a440>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f06bbf0a4d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f06bbf0a560>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f06bbf0a5f0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f06bbf0a680>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f06bbf0a710>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f06bbf0a7a0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f06bbf0a830>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f06bbf0a8c0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f06bbf0a950>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f06bbeb53c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 278224,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1723773184062253125,
+    "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": 0.7378560000000001,
+    "_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": 312,
+    "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:a311f2cf45ce52763cc8f62bbc325ca0c05a8ab05e186ed6767c98ffbe5c86ae
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a96fff48d43afb0905a1078902e0a234e2487523a37e3f5beb1b2e444f45ee21
+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: 2.3.1+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": 265.957062, "std_reward": 19.294392386941496, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-08-16T02:07:27.530812"}