mlp_100000_ppo_1022

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: mlp_100000_ppo_1022
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 261.51 +/- 19.80
+      name: mean_reward
+      verified: false
+---
+
+# **mlp_100000_ppo_1022** Agent playing **LunarLander-v2**
+This is a trained model of a **mlp_100000_ppo_1022** 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 0x7aeb34b4f910>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7aeb34b4f9a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7aeb34b4fa30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7aeb34b4fac0>", "_build": "<function ActorCriticPolicy._build at 0x7aeb34b4fb50>", "forward": "<function ActorCriticPolicy.forward at 0x7aeb34b4fbe0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7aeb34b4fc70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7aeb34b4fd00>", "_predict": "<function ActorCriticPolicy._predict at 0x7aeb34b4fd90>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7aeb34b4fe20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7aeb34b4feb0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7aeb34b4ff40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7aeb404ddec0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1729589076573179371, "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-6.1.85+-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": "2.4.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "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 sha256:98d17907a9ce6fea7c3f77e2068f497c3b9a6d333ef3b95dddeb7aad3ca6d09a
+size 147992

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 0x7aeb34b4f910>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7aeb34b4f9a0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7aeb34b4fa30>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7aeb34b4fac0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7aeb34b4fb50>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7aeb34b4fbe0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7aeb34b4fc70>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7aeb34b4fd00>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7aeb34b4fd90>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7aeb34b4fe20>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7aeb34b4feb0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7aeb34b4ff40>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7aeb404ddec0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1729589076573179371,
+    "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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a93bc17510501c09ba5e331ae9c2125f5578977a9cfe38a7ff906876da79693f
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a12791f350ae6d26d18f75a2fe8b7dddd613db72099df72b3659753dbde0ae55
+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: 2.4.1+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.0
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 261.5126836, "std_reward": 19.795311217445793, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-10-22T09:55:07.605060"}