Comments (1)
Thanks for your question.
In this work, the teacher network (network in network) was trained from scratch by myself.
Maybe there some flaws during the training procedure.
Since the main purpose of this work is verifying the distilling ability.
I simply used default hyperparameters in caffe, and didn't try to optimize the performance.
from model_compression.
Related Issues (8)
- 使用KD训练student network的问题 HOT 1
- Wrong lose function in Hinton method HOT 1
- 不管lr设置多少,迭代100次后loss不在发生变化。
- 迭代100次后loss不在发生变化
- 你好,尝试了你的模型压缩中的知识蒸馏,的确知识蒸馏能提高学生网络的精度,但是训练保存的model文件还是很大呀,而且教师网络越大,最后蒸馏模型训练后得到的权重文件也越大。 HOT 1
- there have a problem when i run the code HOT 1
- Same, Same But Different - Recovering Neural Network Quantization Error Through Weight Factorization
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 model_compression.