MontaR commited on
Commit
385b6e0
1 Parent(s): 878f30f

init LL-v2

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: 277.48 +/- 20.04
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 0x7fedd6a215e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fedd6a21670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fedd6a21700>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fedd6a21790>", "_build": "<function ActorCriticPolicy._build at 0x7fedd6a21820>", "forward": "<function ActorCriticPolicy.forward at 0x7fedd6a218b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fedd6a21940>", "_predict": "<function ActorCriticPolicy._predict at 0x7fedd6a219d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fedd6a21a60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fedd6a21af0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fedd6a21b80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fedd6a16e10>"}, "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": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670487714522459698, "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": -0.004885333333333408, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1472, "n_steps": 1024, "gamma": 0.99999, "gae_lambda": 0.9, "ent_coef": 0.001, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 8, "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": "3.8.15", "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 sha256:4c34819dface5b236e99d36451d9c901b59f84f1e59c8e7fc37ecb45e14051e9
3
+ size 147169
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 0x7fedd6a215e0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fedd6a21670>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fedd6a21700>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fedd6a21790>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fedd6a21820>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fedd6a218b0>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fedd6a21940>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fedd6a219d0>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fedd6a21a60>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fedd6a21af0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fedd6a21b80>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7fedd6a16e10>"
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": 3014656,
46
+ "_total_timesteps": 3000000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1670487714522459698,
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": -0.004885333333333408,
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": 1472,
79
+ "n_steps": 1024,
80
+ "gamma": 0.99999,
81
+ "gae_lambda": 0.9,
82
+ "ent_coef": 0.001,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 8,
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 sha256:5782ab7e0da1046c38fdde9ec9f2eddbe2c0b0ccc3e48c9270a6a9c24226bbc7
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:73a18931bb40592d0df29f1e77f62eadeb88e45f760f4abe98136f9c75e7b2dc
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: 3.8.15
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 (211 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 277.47923157511843, "std_reward": 20.03856672127273, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-08T09:21:34.799500"}