Adder commited on
Commit
30f5e13
1 Parent(s): 49e92ef

Upload PPO LunarLander Trained model first commit.

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: 241.28 +/- 54.61
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 0x7f5452b084c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5452b08550>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5452b085e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5452b08670>", "_build": "<function ActorCriticPolicy._build at 0x7f5452b08700>", "forward": "<function ActorCriticPolicy.forward at 0x7f5452b08790>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5452b08820>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5452b088b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5452b08940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5452b089d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5452b08a60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f5452affe10>"}, "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": 1670688537379077712, "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 sha256:20842f5225970b43af177a554dbb4e8e75aac2ff6af587d34ce0749947f55753
3
+ size 147214
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 0x7f5452b084c0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5452b08550>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5452b085e0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5452b08670>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f5452b08700>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f5452b08790>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5452b08820>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f5452b088b0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5452b08940>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5452b089d0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5452b08a60>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f5452affe10>"
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,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1670688537379077712,
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:de841f55bc4ad8c55921509758c15b027b92d8921ac935f47c10aa40a10911dc
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:ae4b8e5de4bb7009b50650176860572d5fe70c49bbfa1d96d6d233f73f4c8f1f
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 (153 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 241.28487638802184, "std_reward": 54.60920529096829, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-10T18:35:36.858797"}