RTT commited on
Commit
0bdb5ac
1 Parent(s): 658093f

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: 265.80 +/- 20.19
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 0x7f990ab4b160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f990ab4b1f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f990ab4b280>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f990ab4b310>", "_build": "<function ActorCriticPolicy._build at 0x7f990ab4b3a0>", "forward": "<function ActorCriticPolicy.forward at 0x7f990ab4b430>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f990ab4b4c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f990ab4b550>", "_predict": "<function ActorCriticPolicy._predict at 0x7f990ab4b5e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f990ab4b670>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f990ab4b700>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f990ab4b790>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f990ab48450>"}, "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": 1674743025979760321, "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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+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:d53c3ce933599f895c8bc900924149a4321621d20f227f9add8c617cd22de940
3
+ size 147352
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 0x7f990ab4b160>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f990ab4b1f0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f990ab4b280>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f990ab4b310>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f990ab4b3a0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f990ab4b430>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f990ab4b4c0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f990ab4b550>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f990ab4b5e0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f990ab4b670>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f990ab4b700>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f990ab4b790>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7f990ab48450>"
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": 1674743025979760321,
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:a646ce4772b72a84d3cedf8f3191ca7bfc857a2d7fc39de445994526218a8567
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:787a44239118087d2ca0795723287a1703a8cd1c42aea3d382d362504c4cdbf3
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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.8.10
3
+ - Stable-Baselines3: 1.7.0
4
+ - PyTorch: 1.13.1+cu116
5
+ - GPU Enabled: True
6
+ - Numpy: 1.21.6
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (212 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 265.79647604244394, "std_reward": 20.193446348912833, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-26T14:41:34.607318"}