Hi @stubbi , @paf , @antoine , @yhaddad and @grossim Since yesterday me and @jayesh1211 were trying to upload the submission files to the aqora Platform as a Team we were getting a lot of technical issues while uploading the file and ran into errors such VS code not found project.toml not found, so we decided to mail our submission notebook to Jannes on his email @stubbi, just before the final deadline to ensure a fair evaluation, . if the submission has to be reflected on the leaderboard either way, we can upload the same test notebook file on the aqora platform for the leaderboard which was sent to @stubbi via email if you guys can permit some extra time for the upload with some guidelines on how to upload the file

For fair evaluation you can cross check the final uploaded leaderboard results with the file which was send over on email before the deadline

We have achieved a good R^2 R2 score of 0.8189 % along with the cross-section's values. R² Score: 0.8189 for our Hybrid quantum classical Model

Hi @stubbi and @yhaddad Good news we were finally able to upload the submission We took a small subset of the training data and took the entire data for testing we got a good score of 85 for that then we tested the data for the final upload to check whether the training will crash or not we were able to successfully get a score of 81 on the final upload I believe all the time we were trying to diagnose what was the error with testing the data with the entire dataset which was the reason for the crash we believe that due to taking all the test samples caused memory overload We tried many methods to fix this until one proven method finally worked for us . Keeping the deadline in mind and for fair evaluation we did not made any changes to our QML and Classical model . For reference we already have submitted our model notebook to @stubbi via email before deadline if there is need for cross checking the model . We just tried adjusting the data for training and applying methods to reduce testing time for our model which shows our model is robust and scalable We thank you for the patience , advise and the opportunity for participating in this challenge Awaiting the results Thank you Regards

Hi @yhaddad and @stubbi we are still facing the dimensionality error we did what was suggested by @yhaddad and we also took less sample data for training but while uploading it throws an error the only solution for us is to have some compute or HPC power to run the training for all the data samples because our device keeps crashing during the testing Or @stubbi we can send the file to you if you are able to upload it Our model is working well with 20k data sample giving us a score of 82
thank you

Hi @stubbi and @antoine After a lot of debugging and testing we are able to test and run the code using the aqora test command We are getting the same results which I mentioned above a R2 score of 81 After running the notebook with a subset of the original data which can seen in the image . Given that we took only a subset of data due to less compute power of our machine we were able to get a good score We believe if we take all the data there is a possibility of getting good score for the model but given that the training for the large amount of data can be time consuming which I believe is the issue we faced intially with each epoch taking a lot of time One more thing is that we were able to successfully Run and test our notebook and get a good score But there is still issues while uploading the file to the leaderboard Which we believe is due to evaluation and training metrics and data restrictions on the platform backend which takes into account all the data which is giving us errors like dimensionality mismatch We would like to know your thoughts on how to proceed from here Regards

Can you share the specific errors, please?