Johannes Weyel commited on
Commit
c6b702b
·
1 Parent(s): 21e603f

late submission :)

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: 249.44 +/- 24.52
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 0x7f01a29575e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f01a2957670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f01a2957700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f01a2957790>", "_build": "<function ActorCriticPolicy._build at 0x7f01a2957820>", "forward": "<function ActorCriticPolicy.forward at 0x7f01a29578b0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f01a2957940>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f01a29579d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f01a2957a60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f01a2957af0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f01a2957b80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f01a2957c10>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f01a29d1a50>"}, "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": 1674063448952227426, "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-5.15.0-58-generic-x86_64-with-glibc2.29 # 64~20.04.1-Ubuntu SMP Fri Jan 6 16:42:31 UTC 2023", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.24.1", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a7f38ef9dd5027c17941eb349519e4252cbc934aca94659a30c85c9776d3cab3
3
+ size 144787
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppo-LunarLander-v2/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 0x7f01a29575e0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f01a2957670>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f01a2957700>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f01a2957790>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f01a2957820>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f01a29578b0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f01a2957940>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f01a29579d0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f01a2957a60>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f01a2957af0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f01a2957b80>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f01a2957c10>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f01a29d1a50>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "observation_space": {
25
+ ":type:": "<class 'gym.spaces.box.Box'>",
26
+ ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
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": 1674063448952227426,
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:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ca1a715d7622788726d40be1296cc55d032155da30190228ce16ca77c130e916
3
+ size 84829
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:345ca6530071b983f01fcf9ba26d8bb89f6ab02a9cb11c612f377828a12547b5
3
+ size 43393
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 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.0-58-generic-x86_64-with-glibc2.29 # 64~20.04.1-Ubuntu SMP Fri Jan 6 16:42:31 UTC 2023
2
+ - Python: 3.8.10
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.11.0+cu113
5
+ - GPU Enabled: True
6
+ - Numpy: 1.24.1
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (241 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 249.43898254181917, "std_reward": 24.51849243464459, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-18T19:04:52.001526"}