TRiddle commited on
Commit
1b3f528
·
1 Parent(s): a3e8c3a

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: 248.10 +/- 18.62
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 0x7f22d8d5d0d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f22d8d5d160>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f22d8d5d1f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f22d8d5d280>", "_build": "<function ActorCriticPolicy._build at 0x7f22d8d5d310>", "forward": "<function ActorCriticPolicy.forward at 0x7f22d8d5d3a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f22d8d5d430>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f22d8d5d4c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f22d8d5d550>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f22d8d5d5e0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f22d8d5d670>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f22d8d5d700>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f22d8d5f380>"}, "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": 1679419276376491965, "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-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
default-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:31e55776c5d5fbb637ec939243c4b0faee70e75c988ed775b49c3cb3cbb72367
3
+ size 147429
default-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
default-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 0x7f22d8d5d0d0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f22d8d5d160>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f22d8d5d1f0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f22d8d5d280>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f22d8d5d310>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f22d8d5d3a0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f22d8d5d430>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f22d8d5d4c0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f22d8d5d550>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f22d8d5d5e0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f22d8d5d670>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f22d8d5d700>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f22d8d5f380>"
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": 1679419276376491965,
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
+ }
default-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5933acf88e00b5ab1f0bd48f393333bd3559c9936216260b970a7f3fb0c7d11c
3
+ size 87929
default-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c465880b3b89d61206a2366f6445901ac3758c8e9e87c4cefcd807fb3a0bc5bc
3
+ size 43393
default-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
default-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.9.16
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (208 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 248.10294230995396, "std_reward": 18.618892275178975, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-21T17:44:15.288243"}