D3MI4N commited on
Commit
bcb66e7
1 Parent(s): bc273f2

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: 260.85 +/- 14.52
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 0x7c6466f28dc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c6466f28e50>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c6466f28ee0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c6466f28f70>", "_build": "<function ActorCriticPolicy._build at 0x7c6466f29000>", "forward": "<function ActorCriticPolicy.forward at 0x7c6466f29090>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c6466f29120>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c6466f291b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c6466f29240>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c6466f292d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c6466f29360>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c6466f293f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c6466f21700>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718869376994334902, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "dtype": "float32", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_shape": [8], "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]", "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-Dem.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:14aea29cca6d0e4b2d4c5daa8836c4c48bf0ec0f3c3f693ccbe58c1a5a77a0cd
3
+ size 148084
ppo-LunarLander-Dem/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-Dem/data ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7c6466f28dc0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c6466f28e50>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c6466f28ee0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c6466f28f70>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7c6466f29000>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7c6466f29090>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c6466f29120>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c6466f291b0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7c6466f29240>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c6466f292d0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c6466f29360>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c6466f293f0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7c6466f21700>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1015808,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1718869376994334902,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAFqf0L3DzQq6rezTOwTrtDgy4QS7auGEugAAgD8AAIA/pq+avcMJWbq8QoI7K7iDOL97OznyT4i5AACAPwAAgD/N+j89j4ocukaXQ7vvi+A15FYwu35FYjoAAIA/AACAP2Y7Pb3sWfm5AhDsu4XBnTZwT+Q5klQQtgAAgD8AAIA/Ji/NPQqBRLs5pZO8sXgUPB79ijwycgS9AACAPwAAgD/ztjK+CqoUPF6Z3zuWAgO6sTGnvaYu9ToAAIA/AACAP3NDhL0UntA5yv5HON5PFLFKHdO7Vvh3twAAgD8AAIA/80arPVz/Y7puktY6ZpxYNv87FjuO8fO5AACAPwAAgD/A0Mi9KegoumQLsDu2B6s2BMxYuyZhrroAAIA/AACAP6YAtL1c0ym6LZ9OugRZB7XoVS66eLJtOQAAgD8AAIA/QD31Pa8YKz+piw69pZiVviK1jj0lqU+9AAAAAAAAAAAGUAu+cek7u7bLrrvs4pe5/X2ePIuRgjoAAIA/AACAP/0UfL69i6w+CkTEPfxFtb4leMU7BgFSvAAAAAAAAAAAwJouvqlcbbwSRI06vISkOIYH2D2+2rW5AACAPwAAgD8aazU9vQUiPNZ/u70ng5G+Ng6HvTLEJr0AAAAAAAAAAA1IA76P0hI7riLROnKWkrdkdOC87l0PugAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.015808000000000044,
45
+ "_stats_window_size": 100,
46
+ "ep_info_buffer": {
47
+ ":type:": "<class 'collections.deque'>",
48
+ ":serialized:": "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"
49
+ },
50
+ "ep_success_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
+ },
54
+ "_n_updates": 248,
55
+ "observation_space": {
56
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
+ ":serialized:": "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",
58
+ "dtype": "float32",
59
+ "bounded_below": "[ True True True True True True True True]",
60
+ "bounded_above": "[ True True True True True True True True]",
61
+ "_shape": [
62
+ 8
63
+ ],
64
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
65
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
66
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
67
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
68
+ "_np_random": null
69
+ },
70
+ "action_space": {
71
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
72
+ ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 16,
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
+ "lr_schedule": {
96
+ ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
+ }
99
+ }
ppo-LunarLander-Dem/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:adb70262522bd527fb971351c9180f338e573ca15521ef54d006ae45250916e1
3
+ size 88362
ppo-LunarLander-Dem/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2fea09f1856068005a8619003bb3656b3705b9d5fa59f47a9a3ca397c07a3add
3
+ size 43762
ppo-LunarLander-Dem/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-LunarLander-Dem/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.3.0+cu121
5
+ - GPU Enabled: True
6
+ - Numpy: 1.25.2
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (190 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 260.8474459, "std_reward": 14.520291979142327, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-20T08:06:19.275918"}