monobert / README.md
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Push model using huggingface_hub.
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metadata
library_name: xpmir

monoBERT trained on MS-Marco

Passage Re-ranking with BERT (Rodrigo Nogueira, Kyunghyun Cho). 2019. https://arxiv.org/abs/1901.04085

This model has been trained on MsMarco v1

Using the model

The model can be loaded with experimaestro IR

from xpmir.models import AutoModel

# Model that can be re-used in experiments
model, init_tasks = AutoModel.load_from_hf_hub("xpmir/monobert")

# Use this if you want to actually use the model
model = AutoModel.load_from_hf_hub("xpmir/monobert", as_instance=True)
model.rsv("walgreens store sales average", "The average Walgreens salary ranges...")

Results

Dataset AP P@20 RR RR@10 Success@5 nDCG nDCG@10 nDCG@20
msmarco_dev 0.3722 0.0377 0.3774 0.3689 0.5390 0.4767 0.4316 0.4517
trec2019 0.4900 0.7512 0.9426 0.9426 1.0000 0.6933 0.7190 0.6997
trec2020 0.4851 0.6269 0.9354 0.9354 0.9815 0.6935 0.7156 0.6796