由Yoon Kim在《Convolutional Neural Networks for Sentence Classification》中首次提出。该模型主要应用于文...
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BERT fine tune，精度82%，训练：30小时fune tune。serving：单GPU5000词每秒；fasttext，精度81.5%，训...
In this blog, we will train a state-of-the-art Text Classification model using `BERT base uncased`, the word `uncased` means it does not make any difference between `english` and `English`. You can read about the `BERT` model from the Google Research team [here](https:/...
The instructions of building and running the classification trainer and server are described as follows. You may build the docker images from the source or pull the docker images directly from the Docker Hub. Prepare the dataset as a sqlite database The training data is expected to be given as...
You can delve deeper into Deep learning models inAttention, CNN, and what not for Text Classification article, which focuses on different architectures for solving the text classification problem. And here’s one about transfer learning usingBERTandULMFit. ...
"/kaggle/input/jigsaw-multilingual-toxic-comment-classification/jigsaw-unintended-bias-train.csv\n", "/kaggle/input/jigsaw-multilingual-toxic-comment-classification/validation.csv\n", "/kaggle/input/jigsaw-multilingual-toxic-comment-classification/test-processed-seqlen128.csv\n", "/kaggle...
We’ll be using this dataset from Kaggle which concerns a text classification problem. Specifically, given some description of a movie, we need to predict its genre. Each description consists of multiple sentences and there are 27 unique genres (such as action, adult, adventure, animation, biogr...
word2vec+SVM(支持向量机)实现中英文情感分类代码详解就这?word2vec+SVM(支持向量机)实现中英文情感分类代码详解这两篇博客主要是基于中文进行情感分类的,那么本篇博客,我会以这个kaggle项目来介绍如何实现英文长文本情感分类。 1 实验数据 本次数据集来源于kaggle项目“Bag of Words Meets Bags of Popcorn”提供的...
中文长文本分类、短句子分类、多标签分类、两句子相似度(Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short),字词句向量嵌入层(embeddings)和网络层(graph)构建基类,FastText,TextCNN,CharCNN,TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert...