Photons commited on
Commit
9e5f809
1 Parent(s): ba41d10

Upload PPO LunarLander-v2 trained agent

Browse files
.gitattributes CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ - metrics:
12
+ - type: mean_reward
13
+ value: 12.57 +/- 37.00
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: LunarLander-v2
20
+ type: LunarLander-v2
21
+ ---
22
+
23
+ # **PPO** Agent playing **LunarLander-v2**
24
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
25
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
26
+
27
+ ## Usage (with Stable-baselines3)
28
+ TODO: Add your code
29
+
30
+
31
+ ```python
32
+ from stable_baselines3 import ...
33
+ from huggingface_sb3 import load_from_hub
34
+
35
+ ...
36
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 0x7fc58de2be60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc58de2bef0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc58de2bf80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc58de32050>", "_build": "<function ActorCriticPolicy._build at 0x7fc58de320e0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc58de32170>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc58de32200>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc58de32290>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc58de32320>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc58de323b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc58de32440>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fc58de825d0>"}, "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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1653067301.4102688, "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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="}, "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "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:a103016522c76e404a23d09dadd94d3a0255a561bb2cd55e0a8b70292bd9476b
3
+ size 144156
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
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 0x7fc58de2be60>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc58de2bef0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc58de2bf80>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc58de32050>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fc58de320e0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fc58de32170>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc58de32200>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fc58de32290>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc58de32320>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc58de323b0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc58de32440>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fc58de825d0>"
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:": "gASVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 16,
45
+ "num_timesteps": 507904,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1653067301.4102688,
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:": "gASVmAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSxCFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDEAAAAAAAAAAAAAAAAAAAAACUdJRiLg=="
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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 124,
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 sha256:47a771b39ee387c8a3c40011dd779494f1f2d96f0907629154aedd59c1f7ec35
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:b9aadabe938e71c5e689b9b6d83a8f53f29b9283cebeb1e13aab04f93f76a8a5
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-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
2
+ Python: 3.7.13
3
+ Stable-Baselines3: 1.5.0
4
+ PyTorch: 1.11.0+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1d2bbeb396307fc2c85bbe2abb19e6f2034ca9a462c45f55499847b4ad8139a5
3
+ size 237888
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 12.565464430704058, "std_reward": 37.00130639523706, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-20T17:58:16.529480"}