English(EN) How many invoices does it take to teach a model?

发票提取微调：100份发票可达98%准确率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-28 07:57

一项针对发票提取的微调项目发现，使用Qwen2.5-1.5B-Instruct模型配合LoRA，大约100份已标注的发票足以在已知布局上达到98%的准确率。在多达1000份发票上进行训练，仅在已知布局上带来了1.6%的边际改进，而在未知布局上的性能则稳定在77-81%左右，与仅使用提示词的效果相当。有趣的是，在仅25份发票的小型数据集上进行训练，准确率反而低于不进行任何微调仅使用提示词的情况，这表明应将少量已标注的示例包含在提示词中，而不是用于训练。 AI

影响通过了解最佳数据量，提高了特定任务的微调效率，减少了不必要的标注工作。

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dev.to — LLM tag TIER_1 English(EN) · Ritesh Totlani · 2026-10-28 07:57

多少发票才能教会一个模型？

<p>Any fine-tuning project for invoice extraction starts with one question: how many of our invoices do you need before this works? For this task, the measured answer is about 100. Those 100 labelled invoices took the model to 98% on known layouts. The next 900 added 1.6 points, …

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多少发票才能教会一个模型？

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