Hi, I have several questions regarding retrieval-based model
1. How do you get 100 candidates at inference time in calculating P@1, 100
2. At training time, you use all of the utterances from the batch as candidates to minimize the negative log-likelihood of selecting the correct candidate. Why not sample negative examples of a certain proportion. For example, sample 9 negative examples for one positive example. Did you compare these two methods?
Hi, I have several questions regarding retrieval-based model
Looking forward to your reply. Best wishes