bert-based-chinese实现多分类的微调代码 由于每个任务的数据集和模型结构可能不同,因此实现多分类的微调代码有很多种方法。这里给出一种通用的BERT模型微调多分类的代码实现,供参考。 首先,导入需要使用的库: python import torch from torch.utils.data import Dataset, DataLoader from transformers import Bert...
To overcome the data imbalance problem in the\ndistribution of emergency event categories, a novel loss function is proposed\nto improve the performance of the BERT-based model. Meanwhile, to avoid the\nimpact of the extreme learning rate, the Adabound optimization algorithm that\nachieves a ...
BERT模型是通过注意力机制对训练集进行处理。然后,通过Embedding层和Encoder层加载预训练的词向量。 最后,Pooling 层使用BERT 模型来训练两个句子。BERT嵌入层输入层中,输入数据首先通过BERT嵌入部分,将每个单词转换为embeddingwordembeddingword、embeddingpositionembeddingposition和embeddingtokentypeembeddingtokentype。
bert-based-comparison-of-ancient-chinese-poets旧事**ce 上传 在该项目中,选取了12位来自中唐时期的代表性诗人,他们的作品被用来比较其相似性。通过使用Bert模型,研究人员能够对这12位诗人的作品进行深度分析,从而揭示出他们的共同特点和差异。这种比较不仅有助于理解每个诗人的创作风格和主题,还可以为诗歌流派的划分...
All models are character-level based. 3.2. Chinese clinical pre-trained BERT model BERT is pre-trained on Wikipedia and BooksCorpus. However, clinical texts consist of many technical terms which appear seldom in general corpora. To our best knowledge, the public pre-trained BERT model have been...
But word2vec map each word to only one single embedding so it ignores the phenomenon of polysemy(一词多义) in Chinese words. And then we will introduce BERT model to deal with this problem. 3.2 Lattice LSTM Encoder LSTM(Long-Short-Term Memory)是一种设计良好的结构,称为“门”,门包括一个...
A Chinese NLP library based on BERT for sentiment analysis and general-purpose Chinese word segmentation. | 基于 BERT 的中文 NLP 库,用于中文情感倾向分析、通用领域中文分词。 - Cyberbolt/Cemotion
Bert-ChineseNER Introduction 该项目是基于谷歌开源的BERT预训练模型,在中文NER任务上进行fine-tune。 Datasets & Model 训练本模型的主要标记数据,来自于zjy-usas的ChineseNER项目。本项目在原本的BiLSTM+CRF的框架前,添加了BERT模型作为embedding的特征获取层,预训练的中文BERT模型及代码来自于Google Research的bert。
ChineseTextClassificationBasedonBert是一个基于BERT的中文文本二分类模型,用于将文本数据分为正类和负类。该模型利用BERT(Bidirectional Encoder Representations from Transformers)预训练模型作为基础,通过在中文数据集上进行微调,以适应中文文本的特点。 在模型构建过程中,首先需要收集中文文本数据集,包括正类和负类样本。
Aiming at the problems for electricity policy researchers to obtain policies related to specific entities, a deep learning model based on Bert-BiLSTM-CRF is proposed to address the problem by recognizing related entities. The model encodes the power policy text with characters through BERT, extracts...