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--- |
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license: mit |
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language: |
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- zh |
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- en |
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base_model: |
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- Qwen/Qwen2.5-7B-Instruct |
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pipeline_tag: text-generation |
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--- |
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# Dataset Information |
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We introduce an omnidirectional and automatic RAG benchmark, **OmniEval: An Omnidirectional and Automatic RAG Evaluation Benchmark in Financial Domain**, in the financial domain. Our benchmark is characterized by its multi-dimensional evaluation framework, including: |
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1. a matrix-based RAG scenario evaluation system that categorizes queries into five task classes and 16 financial topics, leading to a structured assessment of diverse query scenarios; |
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2. a multi-dimensional evaluation data generation approach, which combines GPT-4-based automatic generation and human annotation, achieving an 87.47% acceptance ratio in human evaluations on generated instances; |
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3. a multi-stage evaluation system that evaluates both retrieval and generation performance, result in a comprehensive evaluation on the RAG pipeline; |
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4. robust evaluation metrics derived from rule-based and LLM-based ones, enhancing the reliability of assessments through manual annotations and supervised fine-tuning of an LLM evaluator. |
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Useful Links: 📝 [Paper](https://arxiv.org/abs/2412.13018) • 🤗 [Hugging Face](https://huggingface.co/collections/RUC-NLPIR/omnieval-67629ccbadd3a715a080fd25) • 🧩 [Github](https://github.com/RUC-NLPIR/OmniEval) |
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We have trained two models from Qwen2.5-7B by the lora strategy and human-annotation labels to implement model-based evaluation.Note that the evaluator of hallucination is different from other four. |
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We provide the evaluator for other metrics except hallucination in this repo. |
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# 🌟 Citation |
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```bibtex |
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@misc{wang2024omnievalomnidirectionalautomaticrag, |
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title={OmniEval: An Omnidirectional and Automatic RAG Evaluation Benchmark in Financial Domain}, |
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author={Shuting Wang and Jiejun Tan and Zhicheng Dou and Ji-Rong Wen}, |
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year={2024}, |
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eprint={2412.13018}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2412.13018}, |
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} |
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``` |
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