nosark commited on
Commit
0d2f5eb
1 Parent(s): 8caa275

Upload PPO LunarLander-v2 trained agent to HuggingFace

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: 267.14 +/- 29.24
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 0x780fa229d000>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x780fa229d090>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x780fa229d120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x780fa229d1b0>", "_build": "<function ActorCriticPolicy._build at 0x780fa229d240>", "forward": "<function ActorCriticPolicy.forward at 0x780fa229d2d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x780fa229d360>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x780fa229d3f0>", "_predict": "<function ActorCriticPolicy._predict at 0x780fa229d480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x780fa229d510>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x780fa229d5a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x780fa229d630>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x780fa223fe00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1703842351214646862, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAI0ROj42EGK85GcDugzuDziX8sK99/MjOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_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-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": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarHopefullyLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f073a698a176f7281efcde83fc2ab6df933d463cbabe4a21faf3b0d9696197de
3
+ size 147358
ppo-LunarHopefullyLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarHopefullyLander-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 0x780fa229d000>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x780fa229d090>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x780fa229d120>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x780fa229d1b0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x780fa229d240>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x780fa229d2d0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x780fa229d360>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x780fa229d3f0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x780fa229d480>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x780fa229d510>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x780fa229d5a0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x780fa229d630>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x780fa223fe00>"
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": 1703842351214646862,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAI0ROj42EGK85GcDugzuDziX8sK99/MjOQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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.discrete.Discrete'>",
72
+ ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 1,
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-LunarHopefullyLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:22ed95cacd0924ec6293776a0fa883329b4862f0715758696fe090feeb091044
3
+ size 88362
ppo-LunarHopefullyLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:74bbbd9e7e12074d53490c196b368b8ad097da2d2fc33120d46be93df3da4dd4
3
+ size 43762
ppo-LunarHopefullyLander-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-LunarHopefullyLander-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: 2.1.0+cu121
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 (187 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 267.13631380000004, "std_reward": 29.240184213184623, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-12-29T10:12:58.540743"}