PecanPi commited on
Commit
384aaaa
·
1 Parent(s): d820f63

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: 263.23 +/- 15.44
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 0x7faa447e1dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7faa447e1e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7faa447e1ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7faa447e1f70>", "_build": "<function ActorCriticPolicy._build at 0x7faa447e5040>", "forward": "<function ActorCriticPolicy.forward at 0x7faa447e50d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7faa447e5160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7faa447e51f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7faa447e5280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7faa447e5310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7faa447e53a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7faa447e5430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7faa447e03c0>"}, "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": 1675779596840837906, "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": 0.995, "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:d5a42552b8c04f5046cf46bdf422525d01cfa65bc330becc04090e1cfc5f1e15
3
+ size 147372
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 0x7faa447e1dc0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7faa447e1e50>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7faa447e1ee0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7faa447e1f70>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7faa447e5040>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7faa447e50d0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7faa447e5160>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7faa447e51f0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7faa447e5280>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7faa447e5310>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7faa447e53a0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7faa447e5430>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc_data object at 0x7faa447e03c0>"
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": 1675779596840837906,
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": 0.995,
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:ca366d3410c034b15bca90d5299b125a2f85f99708da0cfcf8bd1fe81a05b30f
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:55f3fa863f7d1f4104ba048f3bc33d9a494ba33350faad27dfb818ccf78bee09
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 (196 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 263.22997987909235, "std_reward": 15.439001449494157, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-07T14:40:39.035541"}