Comments (1)
Hello,
In my opinion, the goal of adding adversarial perturbation to word embedding is improving the quality of word embedding, which can further improve the classification performance as the paper noted.
Since you are using pre-trained word embedding and want to fix it, I think there is little performance gain compared to the great extra training time brought by the adversarial training.
It may be helpful that adding a fully-connected layer(map vocab size to vocab size) to adapt to the pre-trained word embedding to your task, and you can optimize the parameter of this layer during the adversarial training.
from text-classification.
Related Issues (17)
- data not exist HOT 2
- How can I load data HOT 6
- Wrong output dimension of the embedding_lookup table HOT 1
- Test Accuracy is lower than the Performance in Readme HOT 1
- validation and testing accuracy=0 HOT 2
- Use pre-trained embedding instead of randome one HOT 1
- 关于 Adversarial Training Methods For Semi-Supervised Text Classification代码中的一个问题 HOT 2
- wrong with cnn.py HOT 2
- attn_bi_lstm.py HOT 1
- cannot load the dataset HOT 1
- attn_bi_lstm.py模型的y_hat那里是不是写错了? HOT 1
- Can i ask the editionof the dbpediafile HOT 2
- 怎么存模型呢
- ValueError: Cannot feed value of shape (32, 15) for Tensor 'Placeholder_1:0', which has shape '(?,) HOT 15
- Error in attn_bi_lstm.py while feeding data label during training HOT 2
- adversarial_abblstm.py - validation accuracy: 0% / test accuracy: 0% HOT 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 text-classification.