myu233 commited on
Commit
8a5d6d4
·
1 Parent(s): ba8e662

First commit: Upload 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: 258.92 +/- 14.84
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 0x7f3986cd1a60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3986cd1af0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3986cd1b80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3986cd1c10>", "_build": "<function ActorCriticPolicy._build at 0x7f3986cd1ca0>", "forward": "<function ActorCriticPolicy.forward at 0x7f3986cd1d30>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3986cd1dc0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3986cd1e50>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3986cd1ee0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3986cd1f70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3986c56040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3986c560d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3986c52980>"}, "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": 1678945417567562923, "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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:910cbe2a23dfde13e5f7944ca9cddc119966a9c09de4daca11399d38c5aba126
3
+ size 147425
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppo-LunarLander-v2/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 0x7f3986cd1a60>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3986cd1af0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3986cd1b80>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3986cd1c10>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f3986cd1ca0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f3986cd1d30>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f3986cd1dc0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3986cd1e50>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f3986cd1ee0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3986cd1f70>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3986c56040>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3986c560d0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f3986c52980>"
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": 1678945417567562923,
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
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8131bcde2178e29e4601d663df712e7be0cdb279c1e238c72d92039ed7063d47
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1d87d144897793bcdcdefd6e92068397ae6ab33943f8e0efb5475e4b42159b79
3
+ size 43393
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.9.16
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (220 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 258.92286073431956, "std_reward": 14.843623312540064, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-16T06:42:29.337773"}