Inquiry about training large-scale data
axuan731 opened this issue · comments
Hello,
Thank you very much for your contributions to the code and models. I am currently attempting to train a speaker verification model using a substantial amount of data. However, I have observed that conventional training strategies result in a low accuracy for the model. Therefore, I would like to inquire about how you adjusted parameters such as epochs and learning rates when training a speaker model with 200k speakers. Your insights would be highly appreciated.
The code's training configurations for large-scale and small-scale data remain consistent. To adjust, consider tweaking the learning rate or lowering the margin.