Isaacp commited on
Commit
02c1139
1 Parent(s): bb2d32c

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: 265.35 +/- 18.99
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 0x7f1a36c7d670>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1a36c7d700>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1a36c7d790>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1a36c7d820>", "_build": "<function ActorCriticPolicy._build at 0x7f1a36c7d8b0>", "forward": "<function ActorCriticPolicy.forward at 0x7f1a36c7d940>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1a36c7d9d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f1a36c7da60>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1a36c7daf0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1a36c7db80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1a36c7dc10>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f1a36c73d50>"}, "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": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670799913074164162, "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:a4888938f8deb5b32f1fda571b86931e7d7e29d66dfa76b4f9fd7542b564a850
3
+ size 147208
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 0x7f1a36c7d670>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1a36c7d700>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1a36c7d790>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1a36c7d820>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f1a36c7d8b0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f1a36c7d940>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1a36c7d9d0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f1a36c7da60>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1a36c7daf0>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1a36c7db80>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1a36c7dc10>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f1a36c73d50>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
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": 1000000.0,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1670799913074164162,
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:": "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"
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 sha256:72896396f5df859b1a815abc16c201476024550f9fa0c6e59ad80e80e0202ce0
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:333633f765a1e98962a6e3a337027a1f1989984141c4352a193084f93844ed1e
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 (215 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 265.3536148985089, "std_reward": 18.9883407202081, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-11T23:33:52.415504"}