enlacinglines commited on
Commit
e98ebae
1 Parent(s): 9ca5f2f

yoo, hello moon

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: 249.02 +/- 20.13
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 0x7f4a20e05040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4a20e050d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4a20e05160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4a20e051f0>", "_build": "<function ActorCriticPolicy._build at 0x7f4a20e05280>", "forward": "<function ActorCriticPolicy.forward at 0x7f4a20e05310>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4a20e053a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4a20e05430>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4a20e054c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4a20e05550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4a20e055e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4a20e05670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f4a20e01450>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1676303973832009247, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppolunarlanding.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9ff066ffd5aecc10cccd711b903868cc40f792fce78314e9ac2a1ef4526f87cb
3
+ size 147424
ppolunarlanding/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppolunarlanding/data ADDED
@@ -0,0 +1,95 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7f4a20e05040>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4a20e050d0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4a20e05160>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4a20e051f0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f4a20e05280>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f4a20e05310>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4a20e053a0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4a20e05430>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f4a20e054c0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4a20e05550>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4a20e055e0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4a20e05670>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f4a20e01450>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "observation_space": {
25
+ ":type:": "<class 'gym.spaces.box.Box'>",
26
+ ":serialized:": "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",
27
+ "dtype": "float32",
28
+ "_shape": [
29
+ 8
30
+ ],
31
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
32
+ "high": "[inf inf inf inf inf inf inf inf]",
33
+ "bounded_below": "[False False False False False False False False]",
34
+ "bounded_above": "[False False False False False False False False]",
35
+ "_np_random": null
36
+ },
37
+ "action_space": {
38
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
39
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
40
+ "n": 4,
41
+ "_shape": [],
42
+ "dtype": "int64",
43
+ "_np_random": null
44
+ },
45
+ "n_envs": 16,
46
+ "num_timesteps": 1015808,
47
+ "_total_timesteps": 1000000,
48
+ "_num_timesteps_at_start": 0,
49
+ "seed": null,
50
+ "action_noise": null,
51
+ "start_time": 1676303973832009247,
52
+ "learning_rate": 0.0003,
53
+ "tensorboard_log": null,
54
+ "lr_schedule": {
55
+ ":type:": "<class 'function'>",
56
+ ":serialized:": "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"
57
+ },
58
+ "_last_obs": {
59
+ ":type:": "<class 'numpy.ndarray'>",
60
+ ":serialized:": "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"
61
+ },
62
+ "_last_episode_starts": {
63
+ ":type:": "<class 'numpy.ndarray'>",
64
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
65
+ },
66
+ "_last_original_obs": null,
67
+ "_episode_num": 0,
68
+ "use_sde": false,
69
+ "sde_sample_freq": -1,
70
+ "_current_progress_remaining": -0.015808000000000044,
71
+ "ep_info_buffer": {
72
+ ":type:": "<class 'collections.deque'>",
73
+ ":serialized:": "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"
74
+ },
75
+ "ep_success_buffer": {
76
+ ":type:": "<class 'collections.deque'>",
77
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
78
+ },
79
+ "_n_updates": 248,
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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
ppolunarlanding/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7ec62d66736622313784bcc7ffcee57825c432ee8fb4073e283ab1e5a8cd2e26
3
+ size 87929
ppolunarlanding/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d9da50b253f3c4ba1ddaf3660c1e6a4647e05ffb3b114a7b19e00dbb38b3799c
3
+ size 43393
ppolunarlanding/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ppolunarlanding/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.10
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.21.6
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (216 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 249.01805004544244, "std_reward": 20.127730777277865, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-13T16:25:27.060604"}