Create README.md

README.md

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+---
+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-DPO-1.5B
+
+<!-- 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 Performance
+
+The table below presents the average F1 scores (%) of the ADELIE model across closed IE, open IE, and on-demand IE tasks, as well as its overall performance (%) on general benchmarks. For dataset details, please refer to the paper.
+
+| Model           | Closed IE | Open IE | On-demand IE | General Average Score |
+|-----------------|-----------|---------|--------------|-----------------------|
+| Llama2 7B       | 5.7       | 5.6     | 22.4         | 52.2                  |
+| ADELIE-SFT      | 42.6      | 46.9    | 60.4         | 53.5                  |
+| ADELIE-DPO      | **42.7**      | **47.6**    | **60.5**         | **53.8**                  |
+|-----------------|-----------|---------|--------------|-----------------------|
+| Llama3.2 3B     | 19.1      | 18.5    | 20.8         | 55.5                  |
+| ADELIE-SFT-3B   | **41.8**      | 47.6    | **60.8**         | **55.6**                  |
+| ADELIE-DPO-3B   | 39.2      | **47.8**    | 60.7         | **55.6**                  |
+|-----------------|-----------|---------|--------------|-----------------------|
+| Qwen2.5 1.5B    | 16.5      | 14.2    | 20.5         | 54.6                  |
+| ADELIE-SFT-1.5B | 37.7      | 44.6    | 58.9         | 55.0                  |
+| ADELIE-DPO-1.5B | **38.5**      | **45.6**    | **59.2**         | **55.1**                  |
+
+
+
+### 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]:** Qwen2.5-1.5B
+