DeepCT
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AdeDZY
DeepCT and HDCT uses BERT to generate novel, context-aware bag-of-words term weights for documents and queries.
As the title suggests, Can someone who has this project under running condition, upload the requirements.txt file? thanks
Hi! I would like to plot the training loss of the model, but in the .tfevents-file number of tags that begin with "loss_1" differ from the calculated number of steps...
Hi, I wonder how the "Train data file"-myalltrain.relevant.docterm_recall is constructed?
Hello, First off thank you the provided code! I've been trying to use the code to produce the term weights for some passages and I've noticed that re-running the code...
In your training data, I found that they are all 1-to-1 query-passage pairs, so that the only possible values for QTR or TR are 0 or 1. And in this...
- Whats the difference between collection_pred_1 and collection_pred_2? Is this MSMARCO passage vs document corpora? - Providing a version of each corpus with the bert_term_sample_to_json.py already applied would be easier...
Hi @AdeDZY , To get the new *tf*s, you used `TF_{DeepCT}(t, d) = round(y_{t,d} * 100)`; I was wondering if you tried values other than 100 ? I did similar...
