T5 Base Squad Qg Ae

🚀 lmqg/t5-base-squad-qg-ae 模型卡片

本模型是 t5-base 的微调版本，通过 lmqg 在 lmqg/qg_squad（数据集名称：default）上联合进行问题生成和答案提取任务的微调。

🚀 快速开始

模型概述

模型使用

使用 lmqg 库

from lmqg import TransformersQG

# 初始化模型
model = TransformersQG(language="en", model="lmqg/t5-base-squad-qg-ae")

# 模型预测
question_answer_pairs = model.generate_qa("William Turner was an English painter who specialised in watercolour landscapes")

使用 transformers 库

from transformers import pipeline

pipe = pipeline("text2text-generation", "lmqg/t5-base-squad-qg-ae")

# 答案提取
answer = pipe("generate question: <hl> Beyonce <hl> further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records.")

# 问题生成
question = pipe("extract answers: <hl> Beyonce further expanded her acting career, starring as blues singer Etta James in the 2008 musical biopic, Cadillac Records. <hl> Her performance in the film received praise from critics, and she garnered several nominations for her portrayal of James, including a Satellite Award nomination for Best Supporting Actress, and a NAACP Image Award nomination for Outstanding Supporting Actress.")

📚 详细文档

评估指标

问题生成指标

原始指标文件

问题与答案生成指标

原始指标文件

答案提取指标

原始指标文件

训练超参数

微调期间使用的超参数如下：

• 数据集路径：lmqg/qg_squad
• 数据集名称：default
• 输入类型：['paragraph_answer', 'paragraph_sentence']
• 输出类型：['question', 'answer']
• 前缀类型：['qg', 'ae']
• 模型：t5-base
• 最大长度：512
• 最大输出长度：32
• 训练轮数：6
• 批次大小：32
• 学习率：0.0001
• 混合精度训练：False
• 随机种子：1
• 梯度累积步数：4
• 标签平滑：0.15

完整配置可在 微调配置文件 中找到。

📄 许可证

本模型使用 CC BY 4.0 许可证。

📖 引用

@inproceedings{ushio-etal-2022-generative,
    title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
    author = "Ushio, Asahi  and
        Alva-Manchego, Fernando  and
        Camacho-Collados, Jose",
    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, U.A.E.",
    publisher = "Association for Computational Linguistics",
}