LortsLogan commited on
Commit
605edde
1 Parent(s): 25a9b97

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: 255.06 +/- 17.77
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 0x7822e11ac550>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7822e11ac5e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7822e11ac670>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7822e11ac700>", "_build": "<function ActorCriticPolicy._build at 0x7822e11ac790>", "forward": "<function ActorCriticPolicy.forward at 0x7822e11ac820>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7822e11ac8b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7822e11ac940>", "_predict": "<function ActorCriticPolicy._predict at 0x7822e11ac9d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7822e11aca60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7822e11acaf0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7822e11acb80>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7822e11a87c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712540233947724115, "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:": "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", "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:432c0a90a13b686445f7b9b7eba272e04dff1d9a38a50b3a8ac25955850a6e5e
3
+ size 148080
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v2/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 0x7822e11ac550>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7822e11ac5e0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7822e11ac670>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7822e11ac700>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7822e11ac790>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7822e11ac820>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7822e11ac8b0>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7822e11ac940>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7822e11ac9d0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7822e11aca60>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7822e11acaf0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7822e11acb80>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7822e11a87c0>"
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": 1712540233947724115,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "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"
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-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8c9808a2b2380e9471c17cea642c936a11f19ad105039e2fa2574fbc5d188119
3
+ size 88362
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:98950141a98ffde4331cc9622ae640ac6ad64886fd8419820ed452dbd3592adc
3
+ size 43762
ppo-LunarLander-v2/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-v2/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.2.1+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 (198 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 255.0631656499826, "std_reward": 17.77104094809608, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-08T02:13:38.947823"}