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--- |
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license: apache-2.0 |
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pipeline_tag: text-ranking |
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library_name: lightning-ir |
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base_model: |
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- google/electra-large-discriminator |
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tags: |
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- cross-encoder |
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--- |
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# Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders |
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This model is presented in the paper [Set-Encoder: Permutation-Invariant Inter-Passage Attention for Listwise Passage Re-Ranking with Cross-Encoders](https://huggingface.co/papers/2404.06912). It's a cross-encoder architecture designed for efficient and permutation-invariant passage re-ranking. |
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Code: https://github.com/webis-de/set-encoder |
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We provide the following pre-trained models: |
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| Model Name | TREC DL 19 (BM25) | TREC DL 20 (BM25) | TREC DL 19 (ColBERTv2) | TREC DL 20 (ColBERTv2) | |
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| ------------------------------------------------------------------- | ----------------- | ----------------- | ---------------------- | ---------------------- | |
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| [set-encoder-base](https://huggingface.co/webis/set-encoder-base) | 0.724 | 0.710 | 0.788 | 0.777 | |
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| [set-encoder-large](https://huggingface.co/webis/set-encoder-large) | 0.727 | 0.735 | 0.789 | 0.790 | |
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## Inference |
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We recommend using the `lightning-ir` cli to run inference. The following command can be used to run inference using the `set-encoder-base` model on the TREC DL 19 and TREC DL 20 datasets: |
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```bash |
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lightning-ir re_rank --config configs/re-rank.yaml --config configs/set-encoder-finetuned.yaml --config configs/trec-dl.yaml |
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``` |
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## Fine-Tuning |
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WIP |
