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--- |
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license: mit |
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language: |
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- en |
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base_model: |
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- mistralai/Mistral-7B-Instruct-v0.3 |
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--- |
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# Model Card for `first_mistral` |
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`first_mistral` is a language model trained to act as a listwise reranker, decoding from the first-token logits only to improve efficiency while maintaining effectiveness. |
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`first_mistral` is built on Mistral-7B-Instruct-v0.3, following [FIRST](https://arxiv.org/abs/2406.15657)'s strategy, trained using 40K GPT-4 labeled rerank instances from RankZephyr. |
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More details can be found in the paper. |
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## Model description |
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- **Model type:** A 7B parameter listwise reranker fine-tuned from Mistral-7B-Instruct-v0.3 |
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- **Language(s) (NLP):** Primarily English |
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- **License:** MIT |
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- **Fine-tuned from model:** [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) |
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### Model Sources |
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- **Repository:** https://github.com/castorini/rank_llm |
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- **Paper:** https://arxiv.org/abs/2411.05508 |
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## Evaluation |
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At the time of release, `first_mistral` outperforms the original FIRST implementation on most subsets of the BEIR benchmark. |
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More details that compare other LLM rerankers on more datasets can be found in the paper. |
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| Dataset | FIRST (original) | first_mistral | |
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|----------------|-------------|--------------| |
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| climate-fever | **0.2672** | 0.2417 | |
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| dbpedia-entity | **0.5092** | 0.5033 | |
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| fever | 0.8164 | **0.8413** | |
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| fiqa | 0.4223 | **0.4778** | |
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| hotpotqa | 0.7424 | **0.7705** | |
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| msmarco | 0.4425 | **0.4512** | |
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| nfcorpus | 0.3725 | **0.3816** | |
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| nq | 0.6638 | **0.6985** | |
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| scidocs | 0.2047 | **0.2110** | |
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| scifact | 0.7459 | **0.7769** | |
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| trec-covid | **0.7913** | 0.7666 | |
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| Average | 0.5435 | **0.5564** | |
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## Citation |
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If you find `first_mistral` useful for your work, please consider citing: |
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``` |
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@ARTICLE{chen2024firstrepro, |
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title = title={An Early FIRST Reproduction and Improvements to Single-Token Decoding for Fast Listwise Reranking}, |
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author = {Zijian Chen and Ronak Pradeep and Jimmy Lin}, |
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year = {2024}, |
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journal = {arXiv:2411.05508} |
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} |
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``` |
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If you would like to cite the FIRST methodology, please consider citing: |
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``` |
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@ARTICLE{reddy2024first, |
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title = {FIRST: Faster Improved Listwise Reranking with Single Token Decoding}, |
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author = {Reddy, Revanth Gangi and Doo, JaeHyeok and Xu, Yifei and Sultan, Md Arafat and Swain, Deevya and Sil, Avirup and Ji, Heng}, |
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year = {2024} |
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journal = {arXiv:2406.15657}, |
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} |
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``` |
