neatbullshit commited on
Commit
7cc6ea7
1 Parent(s): c5ba28a

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: 267.67 +/- 11.66
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 0x7faa6dcf7880>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7faa6dcf7910>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7faa6dcf79a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7faa6dcf7a30>", "_build": "<function ActorCriticPolicy._build at 0x7faa6dcf7ac0>", "forward": "<function ActorCriticPolicy.forward at 0x7faa6dcf7b50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7faa6dcf7be0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7faa6dcf7c70>", "_predict": "<function ActorCriticPolicy._predict at 0x7faa6dcf7d00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7faa6dcf7d90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7faa6dcf7e20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7faa6dcf7eb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7faa0c1389c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1684966457147977335, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8919317d61db986a98590a3f7002dff97dab7d940ec1036e5d2fc1fdf8240a07
3
+ size 146759
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7faa6dcf7880>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7faa6dcf7910>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7faa6dcf79a0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7faa6dcf7a30>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7faa6dcf7ac0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7faa6dcf7b50>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7faa6dcf7be0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7faa6dcf7c70>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7faa6dcf7d00>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7faa6dcf7d90>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7faa6dcf7e20>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7faa6dcf7eb0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7faa0c1389c0>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1015808,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1684966457147977335,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "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"
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.015808000000000044,
45
+ "_stats_window_size": 100,
46
+ "ep_info_buffer": {
47
+ ":type:": "<class 'collections.deque'>",
48
+ ":serialized:": "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"
49
+ },
50
+ "ep_success_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
+ },
54
+ "_n_updates": 248,
55
+ "observation_space": {
56
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
+ ":serialized:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
58
+ "dtype": "float32",
59
+ "bounded_below": "[ True True True True True True True True]",
60
+ "bounded_above": "[ True True True True True True True True]",
61
+ "_shape": [
62
+ 8
63
+ ],
64
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
65
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
66
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
67
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
68
+ "_np_random": null
69
+ },
70
+ "action_space": {
71
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
72
+ ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 16,
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
+ "lr_schedule": {
96
+ ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
+ }
99
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cd1409cdbce5a8fba75fc5739e78d2acc575bf17a8470b6e8be57639e98b97ee
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:47b5be9d410ccab29705d5dd6aeb01a138cfefd5a7575e31cf941740616cb455
3
+ size 43329
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 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
2
+ - Python: 3.10.11
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.0.1+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (172 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 267.66727889359333, "std_reward": 11.66362077847876, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-24T22:57:21.280240"}