hhhong commited on
Commit
8efda72
1 Parent(s): 9343d1a

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: 140.68 +/- 95.27
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 0x7a665f765e10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a665f765ea0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a665f765f30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a665f765fc0>", "_build": "<function ActorCriticPolicy._build at 0x7a665f766050>", "forward": "<function ActorCriticPolicy.forward at 0x7a665f7660e0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a665f766170>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a665f766200>", "_predict": "<function ActorCriticPolicy._predict at 0x7a665f766290>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a665f766320>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a665f7663b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a665f766440>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a665f768780>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700979877577261328, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAE1SWz6AP/E+bhxdvgTSqr7qsYK869d4PQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "_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": 3908, "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.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True]", "bounded_above": "[ True True]", "_shape": [2], "low": "[-1. -1.]", "high": "[1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 1, "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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-baseline.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:89135e4c5c32fdf735339576950564373ea1bc956baa5dd74dc189fc7a6b842c
3
+ size 147270
ppo-LunarLander-baseline/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-baseline/data ADDED
@@ -0,0 +1,105 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7a665f765e10>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a665f765ea0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a665f765f30>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a665f765fc0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7a665f766050>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7a665f7660e0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a665f766170>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a665f766200>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7a665f766290>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a665f766320>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a665f7663b0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a665f766440>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7a665f768780>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1000448,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1700979877577261328,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAE1SWz6AP/E+bhxdvgTSqr7qsYK869d4PQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.00044800000000000395,
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": 3908,
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.box.Box'>",
72
+ ":serialized:": "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",
73
+ "dtype": "float32",
74
+ "bounded_below": "[ True True]",
75
+ "bounded_above": "[ True True]",
76
+ "_shape": [
77
+ 2
78
+ ],
79
+ "low": "[-1. -1.]",
80
+ "high": "[1. 1.]",
81
+ "low_repr": "-1.0",
82
+ "high_repr": "1.0",
83
+ "_np_random": null
84
+ },
85
+ "n_envs": 1,
86
+ "n_steps": 1024,
87
+ "gamma": 0.999,
88
+ "gae_lambda": 0.98,
89
+ "ent_coef": 0.01,
90
+ "vf_coef": 0.5,
91
+ "max_grad_norm": 0.5,
92
+ "batch_size": 64,
93
+ "n_epochs": 4,
94
+ "clip_range": {
95
+ ":type:": "<class 'function'>",
96
+ ":serialized:": "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"
97
+ },
98
+ "clip_range_vf": null,
99
+ "normalize_advantage": true,
100
+ "target_kl": null,
101
+ "lr_schedule": {
102
+ ":type:": "<class 'function'>",
103
+ ":serialized:": "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"
104
+ }
105
+ }
ppo-LunarLander-baseline/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7307c2d5a17a48ff38d75a5d75eb734dc2143f9c25b53af5479240cda83bf7c5
3
+ size 88033
ppo-LunarLander-baseline/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b96e61eaf23612d631e6ec973ebd111bab7d4e8d72e6e1db3d9c66a3d0d17176
3
+ size 43567
ppo-LunarLander-baseline/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-baseline/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.1.0+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.23.5
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (157 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 140.68325356628753, "std_reward": 95.27487318564567, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-26T07:14:24.762496"}