This model is to reproduce a variant of TCT-ColBERT-V2 dense retrieval models described in the following paper:

Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. In-Batch Negatives for Knowledge Distillation with Tightly-CoupledTeachers for Dense Retrieval. RepL4NLP 2021 .

Specifically, this checkpoint is finetuned for MS MARCO-V2 passage ranking, and we use this checkpoint as our ``trained'' model for TREC DL 2021 submissions. The initial checkpoint is from a previous one tct_colbert-v2-hnp-msmarco trained on MS MARCO . For fine-tuning, we construct our training data for MS MARCO-V2 passage ranking using this script .