Cross-Encoder for MS Marco
The model can be used for Information Retrieval: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a decreasing order. See SBERT.net Retrieve & Re-rank for more details. The training code is available here: SBERT.net Training MS Marco
Training Data
This model was trained on the MS Marco Passage Ranking task.
Usage
The usage becomes easier when you have SentenceTransformers installed. Then, you can use the pre-trained models like this:
from sentence_transformers import CrossEncoder
model = CrossEncoder('model_name', max_length=512)
scores = model.predict([('Query', 'Paragraph1'), ('Query', 'Paragraph2')])
Performance
In the following table, we provide various pre-trained Cross-Encoders together with their performance on the TREC Deep Learning 2019 and the MS Marco Passage Reranking dataset.
| Model-Name | NDCG@10 (TREC DL 19) | MRR@10 (MS Marco Dev) | Docs / Sec |
|---|---|---|---|
| Version 2 models | |||
| cross-encoder/ms-marco-TinyBERT-L-2-v2 | 69.84 | 32.56 | 9000 |
| cross-encoder/ms-marco-MiniLM-L-2-v2 | 71.01 | 34.85 | 4100 |
| cross-encoder/ms-marco-MiniLM-L-4-v2 | 73.04 | 37.70 | 2500 |
| cross-encoder/ms-marco-MiniLM-L-6-v2 | 74.30 | 39.01 | 1800 |
| cross-encoder/ms-marco-MiniLM-L-12-v2 | 74.31 | 39.02 | 960 |
| Version 1 models | |||
| cross-encoder/ms-marco-TinyBERT-L-2 | 67.43 | 30.15 | 9000 |
| cross-encoder/ms-marco-TinyBERT-L-4 | 68.09 | 34.50 | 2900 |
| cross-encoder/ms-marco-TinyBERT-L-6 | 69.57 | 36.13 | 680 |
| cross-encoder/ms-marco-electra-base | 71.99 | 36.41 | 340 |
| Other models | |||
| nboost/pt-tinybert-msmarco | 63.63 | 28.80 | 2900 |
| nboost/pt-bert-base-uncased-msmarco | 70.94 | 34.75 | 340 |
| nboost/pt-bert-large-msmarco | 73.36 | 36.48 | 100 |
| Capreolus/electra-base-msmarco | 71.23 | 36.89 | 340 |
| amberoad/bert-multilingual-passage-reranking-msmarco | 68.40 | 35.54 | 330 |
| sebastian-hofstaetter/distilbert-cat-margin_mse-T2-msmarco | 72.82 | 37.88 | 720 |
Note: Runtime was computed on a V100 GPU.
- Downloads last month
- 12