hellod035 commited on
Commit
974f948
1 Parent(s): 94c6dd0

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: 261.59 +/- 18.71
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 0x7df36fe78160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7df36fe781f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7df36fe78280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7df36fe78310>", "_build": "<function ActorCriticPolicy._build at 0x7df36fe783a0>", "forward": "<function ActorCriticPolicy.forward at 0x7df36fe78430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7df36fe784c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7df36fe78550>", "_predict": "<function ActorCriticPolicy._predict at 0x7df36fe785e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7df36fe78670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7df36fe78700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7df36fe78790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7df370013440>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708920469769795203, "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": 280, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "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:da38d0cd9a8fa90e1604366f073e002835fae36bd5f208d522728ad961b2bbdf
3
+ size 148084
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 0x7df36fe78160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7df36fe781f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7df36fe78280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7df36fe78310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7df36fe783a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7df36fe78430>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7df36fe784c0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7df36fe78550>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7df36fe785e0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7df36fe78670>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7df36fe78700>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7df36fe78790>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7df370013440>"
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": 1708920469769795203,
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": 280,
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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
98
+ }
99
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2acfe88a648f55bef24fa600b8547052c49245109cb14910584c5b1da31826b1
3
+ size 88362
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:582d9250bdbcd10ff0fb62c7fcff29c0d9d11503eebf8c18fae5d7dfdcf27241
3
+ size 43762
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.1.0+cu121
5
+ - GPU Enabled: True
6
+ - Numpy: 1.25.2
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": 261.5932572868758, "std_reward": 18.705418787726188, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-26T04:33:34.076305"}