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ZhishanQ/QuCo-extractor-0.5B

sourceHugging Faceotherupdated 9mo agoView on Hugging Face
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QuCo-extractor-0.5B

![arXiv](https://arxiv.org/abs/2512.19134) ![GitHub](https://github.com/ZhishanQ/QuCo-RAG) ![License: MIT](https://github.com/ZhishanQ/QuCo-RAG/blob/main/LICENSE)

Model Description

QuCo-extractor-0.5B is a specialized entity extraction model fine-tuned from Qwen2.5-0.5B-Instruct for the QuCo-RAG system. This model extracts knowledge triples (entity-relation-entity) from sentences to support corpus-grounded uncertainty quantification in Retrieval-Augmented Generation.

This model is part of the QuCo-RAG project presented in:

QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation Dehai Min, Kailin Zhang, Tongtong Wu, Lu Cheng [[Paper]](https://arxiv.org/abs/2512.19134) [[Code]](https://github.com/ZhishanQ/QuCo-RAG)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 5e-06
  • —trainbatchsize: 28
  • —evalbatchsize: 32
  • —seed: 42
  • —distributed_type: multi-GPU
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 56
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 2.0

Framework versions

  • —Transformers 4.57.1
  • —Pytorch 2.5.1+cu121
  • —Datasets 4.0.0
  • —Tokenizers 0.22.1