https://github.com/weidafeng/NLU2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Text Classification is the task of assigning a sentence or document an appropriate category. The categories depend on the chosen dataset and can range from topics.
Text Classification problems include emotion classification, news classification, citation intent classification, among others. Benchmark datasets for evaluating text classification capabilities include GLUE, AGNews, among others.
In recent years, deep learning techniques like XLNet and RoBERTa have attained some of the biggest performance jumps for text classification problems.
<span style="color:grey; opacity: 0.6">( Image credit: Text Classification Algorithms: A Survey )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Neural Attentive Bag-of-Entities Model for Text Classification
RoFormer: Enhanced Transformer with Rotary Position Embedding
Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles
Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles
All-but-the-Top: Simple and Effective Postprocessing for Word Representations
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion Recognition
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Augmenting Data with Mixup for Sentence Classification: An Empirical Study
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.