fgeyer commited on
Commit
19f7424
1 Parent(s): f641ca8

PPO agent for LunarLander-v2

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 +/- 21.30
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 0x7fa0a8039750>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa0a80397e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa0a8039870>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa0a8039900>", "_build": "<function ActorCriticPolicy._build at 0x7fa0a8039990>", "forward": "<function ActorCriticPolicy.forward at 0x7fa0a8039a20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fa0a8039ab0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa0a8039b40>", "_predict": "<function ActorCriticPolicy._predict at 0x7fa0a8039bd0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa0a8039c60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa0a8039cf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa0a8039d80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fa0a8d5b380>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1686164382311155359, "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": -0.1468799999999999, "_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": 500, "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-5.19.0-43-generic-x86_64-with-glibc2.35 # 44~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon May 22 13:39:36 UTC 2", "Python": "3.10.6", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu117", "GPU Enabled": "True", "Numpy": "1.24.3", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.26.2"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4fe3cde1fa3fa106d12f027fd1215b449c893aa18203013298ecce9f624ea28b
3
+ size 146855
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 0x7fa0a8039750>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa0a80397e0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa0a8039870>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa0a8039900>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fa0a8039990>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fa0a8039a20>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fa0a8039ab0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa0a8039b40>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fa0a8039bd0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa0a8039c60>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa0a8039cf0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa0a8039d80>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7fa0a8d5b380>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 114688,
25
+ "_total_timesteps": 100000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1686164382311155359,
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": -0.1468799999999999,
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": 500,
55
+ "observation_space": {
56
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
+ ":serialized:": "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",
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 sha256:1d2f077de62eb7908957decd4c67d00263f6472d887a455246ddb3927e13caf9
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:808e1f037da46904eacb81b38ee9a1deb23c2d636cb51ae0dab4453aceb3ac70
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-5.19.0-43-generic-x86_64-with-glibc2.35 # 44~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon May 22 13:39:36 UTC 2
2
+ - Python: 3.10.6
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.0.1+cu117
5
+ - GPU Enabled: True
6
+ - Numpy: 1.24.3
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.26.2
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 267.67013139999995, "std_reward": 21.297454362127205, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-07T12:19:53.300076"}