jesusfbes commited on
Commit
7362d13
1 Parent(s): e240430

First commit of RL model

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: 247.93 +/- 32.87
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 0x7f5ac20f68b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5ac20f6940>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5ac20f69d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5ac20f6a60>", "_build": "<function ActorCriticPolicy._build at 0x7f5ac20f6af0>", "forward": "<function ActorCriticPolicy.forward at 0x7f5ac20f6b80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5ac20f6c10>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5ac20f6ca0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5ac20f6d30>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5ac20f6dc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5ac20f6e50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f5ac20f33c0>"}, "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": 1670753029899745504, "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 sha256:80c6163ad202bd00eb9789851e258bc59ef9b37d576df48954bc09025af285ab
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 0x7f5ac20f68b0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5ac20f6940>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5ac20f69d0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5ac20f6a60>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f5ac20f6af0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f5ac20f6b80>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5ac20f6c10>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f5ac20f6ca0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5ac20f6d30>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5ac20f6dc0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5ac20f6e50>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f5ac20f33c0>"
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": 1670753029899745504,
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:adec588f5267d600dce3ec5db853094011e3e5c12b4827c39bfeb4fc5828c612
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:be74fd5cb5e21e03fc81eda5b6e83946700e086cf8c04c8599c857e18f6cb1af
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 (240 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 247.9312032230786, "std_reward": 32.86531149091467, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-11T10:26:59.789717"}