How to Fine-Tune BERT for Text Classification 这篇论文主要研究了如何在文本分类任务最大化发掘BERT模型的潜力,探索了几种微调BERT的方案。 提供一种常规的微调BERT的解决方案:(1)在任务内数据或者领域内数据进一步预训练BERT;(2)在多个相关任务上进行多任务微调BERT;(3)在目标任务上微调BERT。
进行了如下散步操作:1)进一步在开放域预训练BERT;2)采用多任务方式可选择性地微调BERT;3)在目标任务上微调BERT。同时研究了fine-tuning技术对Bert在长文本任务、隐藏层选择、隐藏层学习率、知识遗忘、少样本学习问题上的影响。 1. 微调策略:不同网络层包含不同的特征信息,哪一层更有助于目标任务?这是一个考虑的...
·提出一种针对Bert的通用fine-tune技术。主要包括三个步骤: (1)在任务相关或者领域相关的训练集上 继续train Bert模型,注意此处不是fine-tuning (2)在相关任务上,通过多任务学习优化Bert `针对特定任务fine-tuning Bert模型 ·研究测试上述fine-tuning技术对Bert在长文本任务、隐藏层选择、隐藏层学习率、知识遗忘、...
BERT用于序列到序列的多标签文本分类 BERT FOR SEQUENCE-TO-SEQUENCE MULTI-LABEL TEXT CLASSIFICATION 引言 我们的主要贡献如下: 1. 我们将BERT的结果作为编码器呈现在MLTC数据集的序列到序列框架中,具有或不具有类上的给定层次树结构。 2. 介绍并实验验证了一种新的MLTC混合模型。 3.我们微调vanilla BERT模型来执...
How to Fine-Tune BERT for Text Classification? demonstrated the 1st approach of Further Pre-training, and pointed out the learning rate is the key to avoid Catastrophic Forgetting where the pre-trained knowledge is erased during learning of new knowledge. We find that a lower learning rate, suc...
How to Fine-Tune BERT for Text Classification?doi:10.1007/978-3-030-32381-3_16Chi SunXipeng QiuXuanjing HuangYige XuSpringer, Cham
This is the code and source for the paperHow to Fine-Tune BERT for Text Classification? In this paper, we conduct exhaustive experiments to investigate different fine-tuning methods of BERT on text classification task and provide a general solution for BERT fine-tuning. ...
I'm attempting to fine-tune gpt-j using the huggingface trainer and failing miserably. I followed the example that references bert, but of course, the gpt-j model isn't exactly like the bert model. The error indicates that the model isn't producing a loss, which is great, except that ...
In this example, we will start with a pre-trainedBERT (uncased)model and fine-tune it on theHate Speech and Offensive Languagedataset. We will then test it on classifying tweets as hate speech, offensive language, or neither. All coding is done inGoogle Colab. ...
Learn how to fine tune the Vision Transformer (ViT) model for the image classification task using the Huggingface Transformers, evaluate, and datasets libraries in Python.