peter1133 commited on
Commit
f31ea3e
1 Parent(s): 4ba189c

add PPO LunarLander-v2 trained agent

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 251.24 +/- 21.06
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
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 0x7fcb61de1820>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcb61de18b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcb61de1940>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcb61de19d0>", "_build": "<function ActorCriticPolicy._build at 0x7fcb61de1a60>", "forward": "<function ActorCriticPolicy.forward at 0x7fcb61de1af0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fcb61de1b80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcb61de1c10>", "_predict": "<function ActorCriticPolicy._predict at 0x7fcb61de1ca0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcb61de1d30>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcb61de1dc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcb61de1e50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fcb61ddc8d0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1673535295261050314, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
lunar.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ef1a626d5850d0fe134cc0e441b19a80838564063e509934b9b2b5710f428058
3
+ size 147416
lunar/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
lunar/data ADDED
@@ -0,0 +1,95 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__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 ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x7fcb61de1820>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fcb61de18b0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fcb61de1940>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fcb61de19d0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fcb61de1a60>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fcb61de1af0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fcb61de1b80>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fcb61de1c10>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fcb61de1ca0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fcb61de1d30>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fcb61de1dc0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fcb61de1e50>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7fcb61ddc8d0>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "observation_space": {
25
+ ":type:": "<class 'gym.spaces.box.Box'>",
26
+ ":serialized:": "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",
27
+ "dtype": "float32",
28
+ "_shape": [
29
+ 8
30
+ ],
31
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
32
+ "high": "[inf inf inf inf inf inf inf inf]",
33
+ "bounded_below": "[False False False False False False False False]",
34
+ "bounded_above": "[False False False False False False False False]",
35
+ "_np_random": null
36
+ },
37
+ "action_space": {
38
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
39
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
40
+ "n": 4,
41
+ "_shape": [],
42
+ "dtype": "int64",
43
+ "_np_random": null
44
+ },
45
+ "n_envs": 16,
46
+ "num_timesteps": 1015808,
47
+ "_total_timesteps": 1000000,
48
+ "_num_timesteps_at_start": 0,
49
+ "seed": null,
50
+ "action_noise": null,
51
+ "start_time": 1673535295261050314,
52
+ "learning_rate": 0.0003,
53
+ "tensorboard_log": null,
54
+ "lr_schedule": {
55
+ ":type:": "<class 'function'>",
56
+ ":serialized:": "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"
57
+ },
58
+ "_last_obs": {
59
+ ":type:": "<class 'numpy.ndarray'>",
60
+ ":serialized:": "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"
61
+ },
62
+ "_last_episode_starts": {
63
+ ":type:": "<class 'numpy.ndarray'>",
64
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
65
+ },
66
+ "_last_original_obs": null,
67
+ "_episode_num": 0,
68
+ "use_sde": false,
69
+ "sde_sample_freq": -1,
70
+ "_current_progress_remaining": -0.015808000000000044,
71
+ "ep_info_buffer": {
72
+ ":type:": "<class 'collections.deque'>",
73
+ ":serialized:": "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"
74
+ },
75
+ "ep_success_buffer": {
76
+ ":type:": "<class 'collections.deque'>",
77
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
78
+ },
79
+ "_n_updates": 248,
80
+ "n_steps": 1024,
81
+ "gamma": 0.999,
82
+ "gae_lambda": 0.98,
83
+ "ent_coef": 0.01,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 4,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
lunar/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fabe061227fd610349bdae99b4f4278c5b0f1841c6b0e8b8cf321c2e86bf1f2d
3
+ size 87929
lunar/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bbeed625204ae42721169e8aa839e54c33f37ffca64d5fbd5606cbec6940485c
3
+ size 43393
lunar/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
lunar/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.16
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.21.6
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (215 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 251.2369785089892, "std_reward": 21.057164787192495, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-12T15:40:34.684216"}