Open tao-sun opened 9 months ago
+1: Not sure what the issue is, but I have similar results from running the baseline, achieves 10.68 SI-SNR for training and 11.00 SI-SNR for validation. I also use the unmodified dataset and have matched the args.
Setting lr=0.001 can solve the problem.
Thank you @tao-sun! That seems to have allowed the baseline to converge to 12.44 SI-SNR on the validation set, which is close to the 12.50 that is reported on the metricsboard.
I ran the baseline model training but performance was not so good as reported in the paper. The SI-SNR.txt is like
Train Valid
10.640213 10.979951 10.750848 11.082418 10.770719 11.054980 10.746675 11.096102 10.768912 11.010266 10.769256 10.998541 10.792813 11.049504 10.786952 10.977900 10.750953 10.791486 10.745253 10.933626 10.740764 10.952813 10.736836 11.025456
Both the dataset and code used were downloaded from the repo and unmodified and data checksum passed. I also compare my args.txt with the one under original one under /baseline_solution/sdnn_delays/Trained and all the params were same. I ran training for two times and got similar results.
Anybody know the cause of this issue or encountered the same situation?
Thanks!