-
-
Notifications
You must be signed in to change notification settings - Fork 350
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Sarcasm Detection for Cross Domain Applications #876
Comments
Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊 |
Finish the previously assigned issue first. |
Hi I would like to be a part of it and give it a try as this is a good opportunity for me as a beginner |
Hi @Rashigera to work on this issue you need to share the approach for solving this problem which should be solely based on deep learning methods. Also you need to confirm with the dataset that you are going to use here for this problem statement. |
Hi @abhisheks008 , I would like to work on this if it isn't already assigned . I'm a beginner and this would be a great opportunity for me.
|
Hi @Sweedle24 thanks for sharing the dataset. In the approach you mentioned about machine learning models as a baseline, can you mention the models you are planning to use? Secondly, for the deep learning models, I'd suggest you to implement at least 3-4 models, compare the accuracy scores to find out the best fitted model for this problem statement. Also can you mention the deep learning models/methods too? |
Hi @abhisheks008 , Thanks for responding |
From the machine learning POV, it's good. But for deep learning models, apart from BERT what other models you are planning to implement here? Need to implement at least 2 more models. |
Hi @abhisheks008, What other models would you recommend exploring? |
Deep Learning Simplified Repository (Proposing new issue)
🔴 Project Title : Sarcasm Detection For Cross Domain Applications.
🔴 Aim : Implement Sarcasm Detection in Cross Domain Applications
🔴 Dataset :
🔴 Approach : Sarcasm Detection in Cross Domain Applications
This project proposes the accuracy and efficiency of ML and NN models trained on one dataset and tested on other dataset. SARC dataset is used for training and amazon review dataset is used for testing the models. This enables Sarcasm detection on Cross Domain applications.
📍 Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.🔴🟡 Points to Note :
✅ To be Mentioned while taking the issue :
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
The text was updated successfully, but these errors were encountered: