mihirdeo16 commited on
Commit
8c8a011
·
1 Parent(s): 197c1c7

Train a basic Lunar 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: 28.58 +/- 114.70
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 0x7f952ba06320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f952ba063b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f952ba06440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f952ba064d0>", "_build": "<function ActorCriticPolicy._build at 0x7f952ba06560>", "forward": "<function ActorCriticPolicy.forward at 0x7f952ba065f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f952ba06680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f952ba06710>", "_predict": "<function ActorCriticPolicy._predict at 0x7f952ba067a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f952ba06830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f952ba068c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f952ba06950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f952b9fee80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1008000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1684958303249868290, "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": -0.008000000000000007, "_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": 189, "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": 16, "n_steps": 1000, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 3, "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-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v1.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b967d0b024624ec393f9663ce9aeb6495cdf630634259b44b897b47a3996f8fa
3
+ size 146753
ppo-LunarLander-v1/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v1/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 0x7f952ba06320>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f952ba063b0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f952ba06440>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f952ba064d0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f952ba06560>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f952ba065f0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f952ba06680>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f952ba06710>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f952ba067a0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f952ba06830>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f952ba068c0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f952ba06950>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7f952b9fee80>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1008000,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1684958303249868290,
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": -0.008000000000000007,
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": 189,
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": 16,
80
+ "n_steps": 1000,
81
+ "gamma": 0.99,
82
+ "gae_lambda": 0.95,
83
+ "ent_coef": 0.0,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 3,
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-v1/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:49d81e0ece0475fd055f50cff65f24e38058487edad7f65054446c3573b966b9
3
+ size 87929
ppo-LunarLander-v1/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:acfddc425b2f0add0b46d5816da4d7e09b8e8638c2f13779a17368ff1f20b68d
3
+ size 43329
ppo-LunarLander-v1/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-v1/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023
2
+ - Python: 3.10.11
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.0.1+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (194 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 28.58433593255473, "std_reward": 114.69542218063275, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-24T20:34:41.045457"}