Hello, I really impressed by the Re2G: Retrive, Rerank, Generate paper. I'm grateful for these good paper.
I have some question about this paper and code.
In this Re2G paper appendix, table4(Re2G hyperparameters) , batch size for DPR and Generation is fixed at 128. However, batch size for reranker is 32.
Why is the batch size different for the reranker?
Also, in re2g code, there is sub-batch forwarding for generation model. According to hypers.retrieve_batch_factor==8 in re2g_hypers.py, there is assertion code like below
Hello, I really impressed by the Re2G: Retrive, Rerank, Generate paper. I'm grateful for these good paper.
I have some question about this paper and code.
In this Re2G paper appendix, table4(Re2G hyperparameters) , batch size for DPR and Generation is fixed at 128. However, batch size for reranker is 32.
Why is the batch size different for the reranker?
Also, in re2g code, there is sub-batch forwarding for generation model. According to
hypers.retrieve_batch_factor==8
in re2g_hypers.py, there is assertion code like belowwhich means it is not the same with each batch size for DPR and generation.
Therefore, is there a specific reason for setting sub-batch for the generation ?
Thank for reading my question.