Bly commited on
Commit
3482641
·
1 Parent(s): 472230a

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: 260.41 +/- 23.76
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 0x7f5a14bab010>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5a14bab0a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5a14bab130>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5a14bab1c0>", "_build": "<function ActorCriticPolicy._build at 0x7f5a14bab250>", "forward": "<function ActorCriticPolicy.forward at 0x7f5a14bab2e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f5a14bab370>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5a14bab400>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5a14bab490>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5a14bab520>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5a14bab5b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5a14bab640>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f5a14badc80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1686119022410720463, "learning_rate": 0.0, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAADqvEL4veX09LvddPFd8d77sxYW8/gDNuwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "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, "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:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "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:f412d091531b1ac7377704761ca28227403d1fac5b923866b8d6d2c2a25bc6db
3
+ size 146128
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 0x7f5a14bab010>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5a14bab0a0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5a14bab130>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5a14bab1c0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f5a14bab250>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f5a14bab2e0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f5a14bab370>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5a14bab400>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f5a14bab490>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5a14bab520>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5a14bab5b0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5a14bab640>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f5a14badc80>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1000448,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1686119022410720463,
30
+ "learning_rate": 0.0,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAADqvEL4veX09LvddPFd8d77sxYW8/gDNuwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.00044800000000000395,
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": 3908,
55
+ "n_steps": 1024,
56
+ "gamma": 0.999,
57
+ "gae_lambda": 0.98,
58
+ "ent_coef": 0.01,
59
+ "vf_coef": 0.5,
60
+ "max_grad_norm": 0.5,
61
+ "batch_size": 64,
62
+ "n_epochs": 4,
63
+ "clip_range": {
64
+ ":type:": "<class 'function'>",
65
+ ":serialized:": "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"
66
+ },
67
+ "clip_range_vf": null,
68
+ "normalize_advantage": true,
69
+ "target_kl": null,
70
+ "observation_space": {
71
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
72
+ ":serialized:": "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",
73
+ "dtype": "float32",
74
+ "bounded_below": "[ True True True True True True True True]",
75
+ "bounded_above": "[ True True True True True True True True]",
76
+ "_shape": [
77
+ 8
78
+ ],
79
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
80
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
81
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
82
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
83
+ "_np_random": null
84
+ },
85
+ "action_space": {
86
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
87
+ ":serialized:": "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",
88
+ "n": "4",
89
+ "start": "0",
90
+ "_shape": [],
91
+ "dtype": "int64",
92
+ "_np_random": "Generator(PCG64)"
93
+ },
94
+ "n_envs": 1,
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 sha256:9730e14af0a33ad4fca4f39c7b2d78984c421e09099eeb6cbe4028c02d64813b
3
+ size 88057
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c3653f93f4a1c7ea6ca9d6c3ffee3bad25e8cdbb9e712c1bd0dc7f5c7929057e
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 (182 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 260.41346000000004, "std_reward": 23.763770615297744, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-08T09:10:34.547292"}