jannikskytt commited on
Commit
e2c64f2
1 Parent(s): 8719f93

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: 240.13 +/- 16.94
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f9d6b073160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9d6b0731f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9d6b073280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9d6b073310>", "_build": "<function ActorCriticPolicy._build at 0x7f9d6b0733a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f9d6b073430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9d6b0734c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9d6b073550>", "_predict": "<function ActorCriticPolicy._predict at 0x7f9d6b0735e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9d6b073670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9d6b073700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9d6b073790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f9d71a47c30>"}, "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": 1673706075419492345, "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-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.7.0", "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 sha256:1e8cc99950fcb34eb467a4395b6af0cb1482f39584915a98957a16c32ade90f2
3
+ size 147420
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.7.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,95 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f9d6b073160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f9d6b0731f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f9d6b073280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f9d6b073310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f9d6b0733a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f9d6b073430>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f9d6b0734c0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f9d6b073550>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f9d6b0735e0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f9d6b073670>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f9d6b073700>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f9d6b073790>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f9d71a47c30>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "observation_space": {
25
+ ":type:": "<class 'gym.spaces.box.Box'>",
26
+ ":serialized:": "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",
27
+ "dtype": "float32",
28
+ "_shape": [
29
+ 8
30
+ ],
31
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
32
+ "high": "[inf inf inf inf inf inf inf inf]",
33
+ "bounded_below": "[False False False False False False False False]",
34
+ "bounded_above": "[False False False False False False False False]",
35
+ "_np_random": null
36
+ },
37
+ "action_space": {
38
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
39
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
40
+ "n": 4,
41
+ "_shape": [],
42
+ "dtype": "int64",
43
+ "_np_random": null
44
+ },
45
+ "n_envs": 16,
46
+ "num_timesteps": 1015808,
47
+ "_total_timesteps": 1000000,
48
+ "_num_timesteps_at_start": 0,
49
+ "seed": null,
50
+ "action_noise": null,
51
+ "start_time": 1673706075419492345,
52
+ "learning_rate": 0.0003,
53
+ "tensorboard_log": null,
54
+ "lr_schedule": {
55
+ ":type:": "<class 'function'>",
56
+ ":serialized:": "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"
57
+ },
58
+ "_last_obs": {
59
+ ":type:": "<class 'numpy.ndarray'>",
60
+ ":serialized:": "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"
61
+ },
62
+ "_last_episode_starts": {
63
+ ":type:": "<class 'numpy.ndarray'>",
64
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
65
+ },
66
+ "_last_original_obs": null,
67
+ "_episode_num": 0,
68
+ "use_sde": false,
69
+ "sde_sample_freq": -1,
70
+ "_current_progress_remaining": -0.015808000000000044,
71
+ "ep_info_buffer": {
72
+ ":type:": "<class 'collections.deque'>",
73
+ ":serialized:": "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"
74
+ },
75
+ "ep_success_buffer": {
76
+ ":type:": "<class 'collections.deque'>",
77
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
78
+ },
79
+ "_n_updates": 248,
80
+ "n_steps": 1024,
81
+ "gamma": 0.999,
82
+ "gae_lambda": 0.98,
83
+ "ent_coef": 0.01,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 4,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null
95
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7ebb91a79c6509075c1afbb3df0b15a415ecb1bcfd577e55660a6086ab1c7f18
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:ffa366b368f390f9590a093eac1db47c5187e217f86c9d95d80180f2cd5e659c
3
+ size 43393
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-5.10.147+-x86_64-with-glibc2.27 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.16
3
+ - Stable-Baselines3: 1.7.0
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 (235 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 240.12555932560304, "std_reward": 16.94227678380821, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-14T14:44:14.792970"}