A few students have asked about how late penalties are calculated. Note the assignment instructions:
Late Submission Policy: 20% marks will be deducted from the total for each day late, up to a total of four days. If five or more days late, a zero mark will be given.
This is not a reduction in the cap on possible marks, as some students have asked. It is a daily late penalty deducted from the raw mark as stated.
For assignments 1 and 2 deductions were calculated on a flat percentage basis, meaning that 20 percent was applied to the total marks available for that assignment, multiplied by the number of days late.
For assignment 3, late penalties were calculated as a percentage of the student's total mark. Therefore, for consistency, we have decided to also apply this system to assignments 1 and 2. Some students will therefore see a small increase in their marks for those assignments, which will be entered in the system before final grades are issued.
I hope that clears things up for everyone.
Astrid
Annotated reports have been uploaded to the system under the same link as previously provided for assignment 1:
https://cgi.cse.unsw.edu.au/~cs9418/18s2/view/
Reports should contain marks for each question and some summary comments. For those students who previously asked for a breakdown of marks, please look at your returned assignments first before emailing if there are any issues.
Cheers, Astrid
Marks for the final assignment are now available. Students generally did well on this assessment.
Students did well on the report writing. Where students lost marks on the report this was due to sections being thin or missing important information. Model performance was scaled relative to the best performing model which had an accuracy rate of 94.9 and MNLP of 0.18 on the test set.
Where students received low overall assignment marks, this was almost always due to something going wrong with the model results. Either the predictions were not in the correct format (e.g. no blank lines between blocks, resulting in zero for model performance), or log probabilities were positive (resulting in zero for MNLP performance).
We are endeavouring to get annotated assignments (2 and 3) uploaded for you to see as soon as possible, however exams-related work is currently taking priority for technical staff. I will email everyone once this is done.
Best of luck with your final exam.
Cheers,
Astrid
[Edit: The uploaded reports will contain your model performance as measured on the test set, and comments so you can see the breakdown.]