saharad commited on
Commit
07d90f3
1 Parent(s): d3cf61e

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: 270.68 +/- 16.37
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 0x7e82fb0ccb80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e82fb0ccc10>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e82fb0ccca0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e82fb0ccd30>", "_build": "<function ActorCriticPolicy._build at 0x7e82fb0ccdc0>", "forward": "<function ActorCriticPolicy.forward at 0x7e82fb0cce50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e82fb0ccee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e82fb0ccf70>", "_predict": "<function ActorCriticPolicy._predict at 0x7e82fb0cd000>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e82fb0cd090>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e82fb0cd120>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e82fb0cd1b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e82fb0c6dc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1689675219702673947, "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": 310, "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-glibc2.31 # 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.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4d761945274809cca8b044ab90844e5b776fffadc8398b539618a52b063392cf
3
+ size 146657
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 0x7e82fb0ccb80>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e82fb0ccc10>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e82fb0ccca0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e82fb0ccd30>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7e82fb0ccdc0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7e82fb0cce50>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e82fb0ccee0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e82fb0ccf70>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7e82fb0cd000>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e82fb0cd090>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e82fb0cd120>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e82fb0cd1b0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7e82fb0c6dc0>"
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": 1689675219702673947,
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": 310,
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": 2048,
81
+ "gamma": 0.99,
82
+ "gae_lambda": 0.95,
83
+ "ent_coef": 0.0,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 10,
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 sha256:91d63a79d5297340fbdbf36b31d6e13218b0d692d99a7ef381938b9a078157f2
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6a838a472be6b5f29e81383a1cb12ed26c7c26a099456c1b886528f65e4ab36c
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-5.15.109+-x86_64-with-glibc2.31 # 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 (173 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 270.6824949893511, "std_reward": 16.369225049797596, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-18T10:50:59.447363"}