Closed Arihant-Bhandari closed 4 months ago
@abhisheks008 hi, can i have a go at this, i feel attention can help boost accuracy for CNN. If i find my work substantial and satisfactory i will PR, if not i will close the issue on my end.
thank you for your time.
Are you planning to enhance this project, https://github.com/abhisheks008/DL-Simplified/tree/main/Chocolate%20Classification%20using%20DL right?
yes @abhisheks008 , the CNN is at 0.86 currently, i think it can be boosted to 0.94 ish with attention, if i do end up achieving this i will start PR.
Follow the same representation like you did in the previous issue. Go ahead with this. Assigned to you @Arihant-Bhandari
@abhisheks008 hi, i think i have completed the project, it has been boosted as i expected, but i want to send over the file without the actual PR for you to see before we make things official with PR.
is it possible, like with an email or on discord ?
@abhisheks008 hi, i think i have completed the project, it has been boosted as i expected, but i want to send over the file without the actual PR for you to see before we make things official with PR.
is it possible, like with an email or on discord ?
Chill dude, make a PR, if any changes are required you can update them flawlessly.
i had 2 possible solutions actually both are same implementation its just model structuring differences. how about i sent them over , you can have a look at them @abhisheks008.
You can sent them over abhishek.opensource@gmail.com. My suggestion is put both of them together in the .ipynb
file, why not showcase a comparison. That'll be insightful.
cool we can do this, i will push them and send a PR in, thanks for listening @abhisheks008
@abhisheks008 i have sent the files over email, pls check, also i noticed someone was working on the README file, issue #526, should i wait for them before updating readme with metrics like i did in the previous project or do it on my own ? i can hand them metrics and image link if they are working on it.
@abhisheks008 i have sent the files over email, pls check, also i noticed someone was working on the README file, issue #526, should i wait for them before updating readme with metrics like i did in the previous project or do it on my own ? i can hand them metrics and image link if they are working on it.
@abhisheks008 i have sent the files over email, pls check, also i noticed someone was working on the README file, issue #526, should i wait for them before updating readme with metrics like i did in the previous project or do it on my own ? i can hand them metrics and image link if they are working on it.
@abhisheks008 i have sent the files over email, pls check, also i noticed someone was working on the README file, issue #526, should i wait for them before updating readme with metrics like i did in the previous project or do it on my own ? i can hand them metrics and image link if they are working on it.
Let's wait for that issue to solved.
hi @abhisheks008 , have you reviewed the codebase, which should i be pushing as PR ?
I checked the code and found that you have overfitted the train dataset as a result it is giving an accuracy of 100% which is an eye catching event. Try to increase the test dataset portion.
hi @abhisheks008 im starting my PR i think i am on the right track here, pls review the codebase, if any changes needed i will be more than glad to do things over. thank you for your patience.
Deep Learning Simplified Repository (Proposing new issue)
:red_circle: Project Title : [Model Enhancement]: Chocolate Classification using DL :red_circle: Aim : enhancing custom CNN model :red_circle: Dataset : https://www.kaggle.com/datasets/siddharthmandgi/chocolate-classification :red_circle: Approach : adding attention as overhead to CNN architecture and using ELU and NADAM in activation and optimizer.
π 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.:red_circle::yellow_circle: Points to Note :
:white_check_mark: To be Mentioned while taking the issue :
Happy Contributing π
All the best. Enjoy your open source journey ahead. π