-
Notifications
You must be signed in to change notification settings - Fork 74
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
Unable to reproduce the paper results! #13
Comments
Same problem here. I've printed the output scores of the learned model with test data = train data, and it turns out that all scores are above 0.5 (i.e. all being classified to 1). One thing I noticed was that examples with label 0 tends to have scores less than 0.51, and those with label 1 tends to have scores above 0.51. |
After months reviewing the data, I can tell you that the partial dataset is filled with errors - if not intentional. For example, in ffmpeg 27295 the method av_get_pixel_fmt() has been later changed to av_get_pix_format() which results in a different graph structure. The fact that so many people can't reproduce the results makes me think Devign is worth throwing out of related works. I will be switching to SARD and only SARD from now on. :) |
@NikolasBielski |
You can find it at https://samate.nist.gov/SARD/. |
Hi,
I'm attempting to reproduce the paper's results, particularly using the provided datasets. On one dataset (under data/input/), I ran the model with the identical experimental settings as described in the paper. However, the model learns nothing. I was hoping you could help me figure out what I'm missing. thanks.
The text was updated successfully, but these errors were encountered: