Comments (11)
We trained it on the two A100 GPUS, and the Map result is about 0.35 in the epoch 24
Hello, I solved this problem, the reason is that the paper used 8 Gpus for training, and I trained on a single card, so I reduced the initial learning rate lr and weight_decay by 8 times, changed to lr=0.75e-4, weight_decay=0.00125, and then decreased the initial learning rate LR and weight_decay by 8 times. Also, enlarge the warmup_iters in lr_config by a factor of eight, to 4000
from maptr.
I have also encounter the same problem
from maptr.
We trained it on the two A100 GPUS, and the Map result is about 0.35 in the epoch 24
from maptr.
Thanks
from maptr.
Hello .I train the model again as your advice,but the Map is about 45.7 in the epoch 24. Could you provicd your single GPU result?Thank you very much
from maptr.
Hello .I train the model again as your advice,but the Map is about 45.7 in the epoch 24. Could you provicd your single GPU result?Thank you very much
First of all, I would like to apologize to you. Due to the computing power of my graphics card, when I adjusted the learning rate, I only trained the author's code for two epochs, and I felt that the accuracy of the second epoch had reached 0.15, so I did not continue the training. Then I went to verify my method, and the accuracy of the training was similar to the results given by the author. My idea is that the results of the multi-card run will be slightly lower than those of the single card, and then I assume that the method of the author can also run on my own computer and produce similar results as in the paper.
from maptr.
Hello .I train the model again as your advice,but the Map is about 45.7 in the epoch 24. Could you provicd your single GPU result?Thank you very much
First of all, I would like to apologize to you. Due to the computing power of my graphics card, when I adjusted the learning rate, I only trained the author's code for two epochs, and I felt that the accuracy of the second epoch had reached 0.15, so I did not continue the training. Then I went to verify my method, and the accuracy of the training was similar to the results given by the author. My idea is that the results of the multi-card run will be slightly lower than those of the single card, and then I assume that the method of the author can also run on my own computer and produce similar results as in the paper.
It seems that the single result is lower than those of the multi-card, maybe it needs a more suitable lr and It confused me.
from maptr.
It seems that the single result is lower than those of the multi-card, maybe it needs a more suitable lr and It confused me.
Yes, you need a good learning rate configuration, you can try it a few times, maybe because our graphics card models are different
from maptr.
Hello .I train the model again as your advice,but the Map is about 45.7 in the epoch 24. Could you provicd your single GPU result?Thank you very much
Could you show me the test results of the training?
from maptr.
from maptr.
I have met this problem as well
from maptr.
Related Issues (20)
- training not proceed after checkpoint saving
- Inquiry Regarding Argoverse2 Dataset Configuration and load_interval Settings
- How can I add trafficlight status in MapTR?
- About the reg_branch in MaptrV2Head HOT 1
- 如何在nuscenes的mini数据集上跑出可视化结果
- nuScenes dataset for MapTRv2 evatuation HOT 2
- can't reproduction evaluation results HOT 2
- 如何使用自己的数据进行训练
- the normal training loss profile
- whats the difference between maptr_tiny_r50_24e_t4 and maptr_tiny_r50_24e?
- intrinsics in transform_3d.py
- Install error HOT 2
- depth supervision code in maptrv2 is not valid? code bug?
- Can not install mmdetection3d HOT 2
- Train on multi-node machine
- Something about layer init parameters
- bev size
- 我安装好环境后出现了初始化报错的问题
- Can't find the definition of hard_voxelize
- queue length都是1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from maptr.