GithubHelp home page GithubHelp logo

Comments (12)

XinWangg avatar XinWangg commented on June 12, 2024

你训练几个epoch呢?

from mobilenetv3-ssd.

CWF-999 avatar CWF-999 commented on June 12, 2024

from mobilenetv3-ssd.

XinWangg avatar XinWangg commented on June 12, 2024

from mobilenetv3-ssd.

CWF-999 avatar CWF-999 commented on June 12, 2024

我到3.62就开始跳动了,下不去了。给更小的学习率也没用

from mobilenetv3-ssd.

XinWangg avatar XinWangg commented on June 12, 2024

from mobilenetv3-ssd.

CWF-999 avatar CWF-999 commented on June 12, 2024

from mobilenetv3-ssd.

liukaigua avatar liukaigua commented on June 12, 2024

请问您给的训练策略能把模型loss收敛到多小?我顶天了到3.7左右就再也降不下去了,不管是加epoch,调整学习率,还是调整batch_size都无法降低了?请问这是什么原因呢?

请问你训练的是哪个数据集?我训练的VOC数据集,在VOC2007_test上的Loss最低也就降到4.36。

from mobilenetv3-ssd.

CWF-999 avatar CWF-999 commented on June 12, 2024

from mobilenetv3-ssd.

liukaigua avatar liukaigua commented on June 12, 2024

VOC2007 和VOC2012一起训练

------------------ 原始邮件 ------------------ 发件人: "lsccccc"<[email protected]>; 发送时间: 2019年11月18日(星期一) 中午11:48 收件人: "shaoshengsong/MobileNetV3-SSD"<[email protected]>; 抄送: "陈文峰"<[email protected]>;"Author"<[email protected]>; 主题: Re: [shaoshengsong/MobileNetV3-SSD] 请问您给的训练策略能把模型loss收敛到多小? (#11) 请问您给的训练策略能把模型loss收敛到多小?我顶天了到3.7左右就再也降不下去了,不管是加epoch,调整学习率,还是调整batch_size都无法降低了?请问这是什么原因呢? 请问你训练的是哪个数据集?我训练的VOC数据集,在VOC2007_test上的Loss最低也就降到4.36。 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or unsubscribe.

还想请问一下您训练的学习率是多少,训练多少个epoch?不胜感激!

from mobilenetv3-ssd.

CWF-999 avatar CWF-999 commented on June 12, 2024

from mobilenetv3-ssd.

liukaigua avatar liukaigua commented on June 12, 2024

用的余弦退火学习率调整策略,300epoch,初始0.01

------------------ 原始邮件 ------------------ 发件人: "lsccccc"<[email protected]>; 发送时间: 2019年11月18日(星期一) 下午3:59 收件人: "shaoshengsong/MobileNetV3-SSD"<[email protected]>; 抄送: "陈文峰"<[email protected]>;"Author"<[email protected]>; 主题: Re: [shaoshengsong/MobileNetV3-SSD] 请问您给的训练策略能把模型loss收敛到多小? (#11) VOC2007 和VOC2012一起训练 … ------------------ 原始邮件 ------------------ 发件人: "lsccccc"<[email protected]>; 发送时间: 2019年11月18日(星期一) 中午11:48 收件人: "shaoshengsong/MobileNetV3-SSD"<[email protected]>; 抄送: "陈文峰"<[email protected]>;"Author"<[email protected]>; 主题: Re: [shaoshengsong/MobileNetV3-SSD] 请问您给的训练策略能把模型loss收敛到多小? (#11) 请问您给的训练策略能把模型loss收敛到多小?我顶天了到3.7左右就再也降不下去了,不管是加epoch,调整学习率,还是调整batch_size都无法降低了?请问这是什么原因呢? 请问你训练的是哪个数据集?我训练的VOC数据集,在VOC2007_test上的Loss最低也就降到4.36。 — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or unsubscribe. 还想请问一下您训练的学习率是多少,训练多少个epoch?不胜感激! — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub, or unsubscribe.

感谢,我再去试试。

from mobilenetv3-ssd.

shaoshengsong avatar shaoshengsong commented on June 12, 2024

It is recommended that git clone this version
https://github.com/shaoshengsong/MobileNetV3-SSD-Compact-Version
loss =1.8,1,9

from mobilenetv3-ssd.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo 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.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.