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code for paper 《RankingGPT: Empowering Large Language Models in Text Ranking with Progressive Enhancement》

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Description

This is the official code for paper RankingGPT: Empowering Large Language Models in Text Ranking with Progressive Enhancement.

Requirements

transformers==4.28.1
datasets
pyserini
torch==1.13.1

Data

  • ./datasets/text_pairs.json: Weakly supervised text pairs

  • ./datasets/msmarco.json: Supervised fine-tuning data

  • ./rankdata/trec19: Top-1000 query-document pairs recalled by BM25

Two-stage Training

Pretrain

bash pretrain.sh bigscience/bloom-560m bloom-560m BloomBlock

SFT

bash sft.sh ./outputs_pretrain_bloom-560m bloom-560m 16 BloomBlock

Evaluation

bash eval.sh ./outputs_sft_bloom-560m trec19 bloom-560m

Results

Ranking results (NDCG@10) of the top-1000 candidate documents recalled by BM25.

DL19 DL20 BEIR url
MonoBERT-340M 72.3 70.3 50.5 huggingface
MonoT5-220M 71.5 69.7 49.3 huggingface
MonoT5-770M 73.2 71.2 53.1 huggingface
MonoT5-3B 72.8 74.5 54.6 huggingface
RankT5-770M - - 53.7 huggingface
RankLLaMA 74.6 76.6 52.5 huggingface
RankingGPT-bloom-560m 75.3 73.2 53.7 huggingface modelscope
RankingGPT-bloom-1b1 75.6 73.2 54.5 huggingface modelscope
RankingGPT-bloom-3b 76.8 73.6 56.2 huggingface modelscope
RankingGPT-bloom-7b 77.3 74.6 56.6 huggingface modelscope
RankingGPT-llama2-7b 76.2 76.3 57.8 huggingface modelscope
RankingGPT-baichuan2-7b 75.9 74.3 57.5 huggingface modelscope
RankingGPT-qwen-7b 75.8 74.3 58.3 huggingface modelscope

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code for paper 《RankingGPT: Empowering Large Language Models in Text Ranking with Progressive Enhancement》

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