Commit
•
cf141c1
1
Parent(s):
04fa6fa
Upload PPO LunarLander-v2 trained agent
Browse files- README.md +37 -0
- config.json +1 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +99 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +9 -0
- replay.mp4 +0 -0
- results.json +1 -0
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: 262.98 +/- 9.72
|
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 0x7ae4af0a2ef0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ae4af0a2f80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ae4af0a3010>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ae4af0a30a0>", "_build": "<function ActorCriticPolicy._build at 0x7ae4af0a3130>", "forward": "<function ActorCriticPolicy.forward at 0x7ae4af0a31c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ae4af0a3250>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ae4af0a32e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ae4af0a3370>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ae4af0a3400>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ae4af0a3490>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ae4af0a3520>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ae4af9d1180>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712664021611996414, "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": 310, "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:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "n_steps": 2048, "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": 10, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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 sha256:8f6948ff66dd3587697cb47a7681d51e9c994ef6fef3746debea6a7748b4f248
|
3 |
+
size 148273
|
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 0x7ae4af0a2ef0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ae4af0a2f80>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ae4af0a3010>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ae4af0a30a0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7ae4af0a3130>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7ae4af0a31c0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7ae4af0a3250>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ae4af0a32e0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7ae4af0a3370>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ae4af0a3400>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ae4af0a3490>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7ae4af0a3520>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7ae4af9d1180>"
|
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": 1712664021611996414,
|
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": 310,
|
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:": "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",
|
73 |
+
"n": "4",
|
74 |
+
"start": "0",
|
75 |
+
"_shape": [],
|
76 |
+
"dtype": "int64",
|
77 |
+
"_np_random": "Generator(PCG64)"
|
78 |
+
},
|
79 |
+
"n_envs": 16,
|
80 |
+
"n_steps": 2048,
|
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": 10,
|
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 sha256:0588beffa206b592ce9e1f774a144324e29cf132a43deb464468557bdf2507df
|
3 |
+
size 88362
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9fbac675ecdf2fe2339e51d55740083deb9458ab63225fa49121ddced1eb0637
|
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 (180 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 262.9750812, "std_reward": 9.72303534177781, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-04-09T12:45:07.254450"}
|