dssm's People
Forkers
polaris79 marziehsaeidi kai-gao raojun06 ala-n duoledaddy andysdc deeplearningsky ywd3169 yuan39 imzwz jianweicui lightsilver shihuaxing viksit gusuperstar oliviershi meccy leihao612 liaozy zoumingithub abell25 cutecha isnowalarm zhongyunuestc renyi533 joseph-chan hanxiao baccanoeva chunlinx lijiankou novellll zhujiahui hkxiron tjucxq kakaruihoho wangjianyong trungtrinh44 gnusi ambier glbreeze zhouyonglong talentlei gaoyz0625 wudapeng268 alex-yip innerface zhengzhenxian williamwhe leoruc2016 zbn123 brucekyle99 qwzhong1988 czhiming hins austin-w lddsdu nevg9 irenehere szha381 kekeburning wonderlzy qianmacao geogreff watereals meishuguo shenyong123 xinshu omcar17 ithinkseu wangdf62 yier2333 sampsonguo lihengtianxia iwii0425 haerbinwyzhaha buptygz youhebuke lydonl jackyshiwang xinhen shmilychomi hurun woaipichuli tiffendssm's Issues
test-loss not stable
Hi, I see that in your code both train and test loss are the same, which is: 1. computed prob
of the positive sample using softmax function, 2. compute its logloss against label (always 1).
My question is, the first step depends on randomly sampled negative samples, which makes the losses jumps during my training. I'm curious if you have tried to compute logloss using positive sample's logit only (not depend on negative samples)?
Why doesn't the training loss decrease ?
There are two parts in my loss. One is the dssm loss and the other is the reg loss. However even the dssm loss is much bigger than the reg loss, it does not even change while the reg loss is slowly decressing. Has anyone encountered the same problem?
data request
where to download data used in dssm?
why my train loss after 1 Epoch equal 0 and auc =1.
when i train this my loss fast equal 0 and auc=1?
is tile useful?
In dssm.py
temp = tf.tile(doc_y, [1, 1])
I think temp is equal to doc_y
is tile useful?
how to run this?
can you explain each file?
And i hope that now you can provide data sources.
Data used for this repo
Hi @LiahA, thanks for sharing the code for your implementation. It is good to compare performance.
Can you share the data used for training your model? Can it be generated using another script? I did see that you've added an ignore to the data folder in your .gitignore file. Did you use the MS Marco dataset as done in the paper?
Thanks.
dimension does not match during SparseTensorDenseMatMul
When running dssm/single/dssm_v3.py, InvalidArgumentError happens at SparseTensorDenseMatMul with the info "Cannot multiply A and B because inner dimension does not match". I check the code and find that maybe the shape for SparseTensorValue should be np.array([BS, TRIGRAM_D], np.int64) not np.array([BS, TRIGRAM_D], np.int64). Does anyone has the same problems?
why i can't see label in the code
how to discrimate the positive & negtive example in the code dssm_v2.py?
i don't see any label.
How does your train_data for dssm organazed? Or the data format
I have seen your demo dssm/single/dssm_v3.py, and want to know how your data be organazed. For example, what the format of query.train.pickle ?
why my train loss ,after 4or5 epoch ,softmax value equal nan。
why my train loss ,after 4or5 epoch ,softmax value equal nan。
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.