OGSneakybot commited on
Commit
1e84992
·
1 Parent(s): 12e7895

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: 269.12 +/- 17.42
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 0x7f9e2fd85430>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9e2fd854c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9e2fd85550>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9e2fd855e0>", "_build": "<function ActorCriticPolicy._build at 0x7f9e2fd85670>", "forward": "<function ActorCriticPolicy.forward at 0x7f9e2fd85700>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9e2fd85790>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9e2fd85820>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9e2fd858b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9e2fd85940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9e2fd859d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9e2fd85a60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f9e2fd7d900>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1675278868858166546, "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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6c6a66bfe7daec8f00a8b167a796963e8e6030b5a640cba4efbedc7f880a5f5e
3
+ size 147416
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 0x7f9e2fd85430>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9e2fd854c0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9e2fd85550>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9e2fd855e0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f9e2fd85670>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f9e2fd85700>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9e2fd85790>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9e2fd85820>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f9e2fd858b0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9e2fd85940>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9e2fd859d0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9e2fd85a60>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f9e2fd7d900>"
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": 1675278868858166546,
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:fda0e727af56f66eaab97e6bd359fff7799eb0bdba9787ec6b508272bd698a76
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:a53469e09f6f16b9df02076284d87d059dec5d47ac8e5aba858c2288c278d756
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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.10
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 (213 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 269.1215422868114, "std_reward": 17.419166120257465, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-01T19:36:00.581215"}