cverluise commited on
Commit
101cdf8
β€’
1 Parent(s): 4d4b242

πŸš€ Lunar lander ready.

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: 259.08 +/- 25.10
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7fca60b50550>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fca60b505e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fca60b50670>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fca60b50700>", "_build": "<function ActorCriticPolicy._build at 0x7fca60b50790>", "forward": "<function ActorCriticPolicy.forward at 0x7fca60b50820>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fca60b508b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fca60b50940>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fca60b509d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fca60b50a60>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fca60b50af0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fca60b4e3f0>"}, "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": 1671465742255615123, "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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3df59edaac1d1796c3de5ff4a633cb830f152fecaa1d3f755873ef0df6fde31f
3
+ size 147210
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.2
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7fca60b50550>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fca60b505e0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fca60b50670>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fca60b50700>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fca60b50790>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fca60b50820>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fca60b508b0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fca60b50940>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fca60b509d0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fca60b50a60>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fca60b50af0>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fca60b4e3f0>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
26
+ "dtype": "float32",
27
+ "_shape": [
28
+ 8
29
+ ],
30
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
31
+ "high": "[inf inf inf inf inf inf inf inf]",
32
+ "bounded_below": "[False False False False False False False False]",
33
+ "bounded_above": "[False False False False False False False False]",
34
+ "_np_random": null
35
+ },
36
+ "action_space": {
37
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
38
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 1015808,
46
+ "_total_timesteps": 1000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1671465742255615123,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAIDWjb17qpu6mgO2Nne2nDF42vk5Wn3VtQAAgD8AAIA/AGhxO8N1SrpMYhG5Rknssw59LTskpCg4AACAPwAAgD+aKAy9Kbw/usrnfLoT9eW1zV8qO06HkzkAAIA/AACAP5o8qTxSENa5G2Twus3p0jTGNYm7PbQNOgAAgD8AAIA/5k5sPVyDc7qVy7i6wLWptRKOiLnzdtg5AACAPwAAgD/Nz9s8w91guroH5bO8MDyvm+OEu75NqjMAAIA/AACAP2YWNTtIr4O691tCOikGQDUxZBC4y1xiuQAAgD8AAIA/AJd2vSkQSbqOLtE7RM/YN7z0iDrIgRM2AACAPwAAgD9mWAo9KWA7uqbS+rJk4QSxJJ+buqn/uzMAAIA/AACAP4DFSr4ex58+sO2NPq3kU773kno8joOhPQAAAAAAAAAA5ppuvq2mYD/VNEy9VbeuvhB+BL7Zury7AAAAAAAAAACA/0G9Uoqqu+A+Tz1VuJU8iNkbvVXGfT0AAIA/AACAP5oVPr2Pale6xhPFO2fB7je7kXO7emhfNgAAgD8AAIA/syZUPa5tmrrEkJa7HeVZOM62mbntEnQ4AACAPwAAgD+zJrO9X5R9P+oLcL5Vj9W+VMquvcpMmL0AAAAAAAAAAJoneT17gqW6LmUoumQZQzY3lh06HhxBOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.015808000000000044,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "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"
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 248,
79
+ "n_steps": 1024,
80
+ "gamma": 0.999,
81
+ "gae_lambda": 0.98,
82
+ "ent_coef": 0.01,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 4,
87
+ "clip_range": {
88
+ ":type:": "<class 'function'>",
89
+ ":serialized:": "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"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c4bee2bd6c654aab7445d4144999e2edeb2108d82a76d6d3381bc705b9d719cf
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8d61323986632e9976d0146d1460ffd248c933a02168acc5f82385b82c929ae4
3
+ size 43201
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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
2
+ Python: 3.8.16
3
+ Stable-Baselines3: 1.6.2
4
+ PyTorch: 1.13.0+cu116
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
Binary file (241 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 259.0788358055697, "std_reward": 25.10125650073183, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-19T16:35:09.111134"}