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---
license: llama2
datasets:
- ACE05
- conll2003
- conll2012_ontonotesv5
- rams
- tacred
- fewrel
- maven
language:
- en
metrics:
- f1
pipeline_tag: text-generation
tags:
- text-generation-inference
- Information Extraction
- IE
- Named Entity Recogniton
- Event Extraction
- Relation Extraction
- LLaMA
---
# Model Card for ADELIE-SFT
<!-- Provide a quick summary of what the model is/does. -->
<p align="justify">
We introduce <b>ADELIE</b> (<b>A</b>ligning large language mo<b>DEL</b>s on <b>I</b>nformation <b>E</b>xtraction), an aligned LLM that effectively solves various IE tasks, including closed IE, open IE, and on-demand IE. We first collect and construct a high-quality alignment corpus <font face="Verdana">IEInstruct</font> for IE. Then we train ADELIE<sub>SFT</sub> using instruction tuning on <font face="Verdana">IEInstruct</font>. We further train ADELIE<sub>SFT</sub> with direct preference optimization (DPO) objective, resulting in ADELIE<sub>DPO</sub>. Extensive experiments on various held-out IE datasets demonstrate that our models (ADELIE<sub>SFT</sub> and ADELIE<sub>DPO</sub>) achieve state-of-the-art (SoTA) performance among open-source models. We further explore the general capabilities of ADELIE, and experimental results reveal that their general capabilities do not exhibit a noticeable decline.
- 📖 Paper: [ADELIE: Aligning Large Language Models on Information Extraction](https://arxiv.org/abs/2405.05008)
</p>
- 🐧 Github: [THU/ADELIE](https://github.com/THU-KEG/ADELIE/tree/main)
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** Yunjia Qi, Hao Peng, Xiaozhi Wang, Bin Xu, Lei Hou, Juanzi Li
- **Model type:** Text Generation
- **Language(s) (NLP):** English
- **License:** LLaMA2 License for the base model.
- **Finetuned from model [optional]:** LLaMA2-7B
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