Comments (1)
Hi,
thanks for your comment.
That's right, if you keep updating the same prompt, catatstrophic forgetting will occur.
Please refer to this and this.
Even in my experience, prompt selection is very strongly optimized for the first task.
Also, I don't think CIFAR100 is a very good dataset.
No matter how many classes in each task are changed (shuffle), the accuracy does not make much difference, and still only the same prompts are selected.
In addition, I tested all combinations of random selection and fixed order selection, but there was no significant difference in performance.
If you have any additional comments, please feel free to let me know.
Best,
Jaeho Lee.
from l2p-pytorch.
Related Issues (12)
- Reproduce for Dual-Prompt HOT 3
- vit_base_patch16_224 HOT 3
- Question about loss function HOT 1
- L2P reproduce (about freeze layer & shuffle argument)
- Loss is NaN. HOT 1
- Diversifying prompt-selection HOT 2
- Implementation about domain incremental learning? HOT 2
- How to use the rehearsal buffer? HOT 1
- Question about the classification head layer HOT 3
- The Prompt parameters of five_datasets in pytorch-implementation is different from that given in paper
- Doubts regarding Transferring previous learned prompt params to the new prompt 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 l2p-pytorch.