HuggingFace DeepRL - unit1

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: 247.60 +/- 24.15
+      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 0x784f6ce348b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x784f6ce34940>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x784f6ce349d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x784f6ce34a60>", "_build": "<function ActorCriticPolicy._build at 0x784f6ce34af0>", "forward": "<function ActorCriticPolicy.forward at 0x784f6ce34b80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x784f6ce34c10>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x784f6ce34ca0>", "_predict": "<function ActorCriticPolicy._predict at 0x784f6ce34d30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x784f6ce34dc0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x784f6ce34e50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x784f6ce34ee0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x784f6cfd7f80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1709388271475907264, "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]", "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-6.1.58+-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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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:e841cbdbef36bc76434ac8dfacfba618341baad98d63ce34e43cab318022450b
+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 0x784f6ce348b0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x784f6ce34940>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x784f6ce349d0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x784f6ce34a60>",
+        "_build": "<function ActorCriticPolicy._build at 0x784f6ce34af0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x784f6ce34b80>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x784f6ce34c10>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x784f6ce34ca0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x784f6ce34d30>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x784f6ce34dc0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x784f6ce34e50>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x784f6ce34ee0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x784f6cfd7f80>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1709388271475907264,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJoZ9DzsQOA+3dkWvkUamb5UD6O9KwkZPQAAAAAAAAAAmtHTvOaZtz/9ftu+kPTbPdDX4zyt5IM9AAAAAAAAAACA9+w9VylEP7kSHDxVTJ6+Rf2XPYpk5b0AAAAAAAAAANo/L74vYrU/WOLXvluA5b7Qdg++CO4mvgAAAAAAAAAAGgUhPfifjD00w8w7V3hsvg/TYj3UY0Y8AAAAAAAAAADNVfK83Mc8vENtc71LMPy9DZmbPVUgCj8AAIA/AACAPxrDsr1F9A4/9G4UvXX5sr43oMg7p0QhPQAAAAAAAAAAALwLPE8RTry+SxK7jrEePX1VuT11yvu9AACAPwAAgD9m/XG9j8oYupQdFLhgHhazBml1u+eALjcAAIA/AACAP8A91L3DyWK6E7ygukGnKbbZFuU5hd64OQAAgD8AAIA/Zi44vI9+XrrExYs55BtINAGLzbr87qG4AACAPwAAgD/dbIQ+XLpHP2XN/r3kamK+LxAJPnEaRL4AAAAAAAAAAGY1sTybDIc9E0prvrSaV76ODvq81UKZvQAAAAAAAAAAs3Z3PUU0kT81NvE9EiC6vopYEj4Paqk9AAAAAAAAAACatPa9cbouu7CtDz42/yi+G3qwvBbzF78AAIA/AACAP/OLSD734B8/+uTWvfHaW76wxLI8GxafvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.015808000000000044,
+    "_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]",
+        "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 sha256:8c838ecd365c3142b3be82362cded86aedbf202ae9bff8f933677e5ae7a2e678
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cbcf9135f088bf2213654d493437943f9ec53536c061b73c96d141b844f574da
+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-6.1.58+-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: 2.1.0+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": 247.59797600000002, "std_reward": 24.149304258018955, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-02T14:37:54.822586"}