merryjane commited on
Commit
a486ce1
1 Parent(s): 11e6279

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: 267.84 +/- 27.77
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 0x79d82ae80790>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79d82ae80820>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79d82ae808b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79d82ae80940>", "_build": "<function ActorCriticPolicy._build at 0x79d82ae809d0>", "forward": "<function ActorCriticPolicy.forward at 0x79d82ae80a60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79d82ae80af0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79d82ae80b80>", "_predict": "<function ActorCriticPolicy._predict at 0x79d82ae80c10>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79d82ae80ca0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79d82ae80d30>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79d82ae80dc0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79d82ae7d380>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1691462066482451694, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAID0wb3ohcS8ThH1Ov6IZTvZ2pe8W4WPvAAAAAAAAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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, "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": 1, "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-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "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-unit1.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:08f4e37461dbb9603c106d2120fb8863285cd8b864343d1e6a7c361619970501
3
+ size 146032
ppo-LunarLander-v2-unit1/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v2-unit1/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 0x79d82ae80790>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79d82ae80820>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79d82ae808b0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79d82ae80940>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x79d82ae809d0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x79d82ae80a60>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x79d82ae80af0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79d82ae80b80>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x79d82ae80c10>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79d82ae80ca0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79d82ae80d30>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x79d82ae80dc0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x79d82ae7d380>"
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": 1691462066482451694,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAID0wb3ohcS8ThH1Ov6IZTvZ2pe8W4WPvAAAAAAAAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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
+ "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": 1,
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-unit1/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c8ff621feda15351c09edc563c68d90fba6ccb9397c7e0aa01cd4db6fa78ef72
3
+ size 87929
ppo-LunarLander-v2-unit1/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:97f3235960526fe94d6982a0e1a19d3306868f6612a5a830b8dce9b2c7bdcee8
3
+ size 43329
ppo-LunarLander-v2-unit1/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-unit1/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
2
+ - Python: 3.10.12
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 (116 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 267.83945, "std_reward": 27.77206642752498, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-08T03:17:14.580497"}