[자연어 용어 정리] 자연어 용어
인퍼런스(inference)
학습을 마친 모델로 실제 과제를 수행하는 행위나 그 과정
모델을 실전에 투입하는 것
ClassificationDataset 클래스
인스턴스들은 input_ids, attention_mask, token_type_ids, label 4가지 필드를 가리킨다.
Random Seed
난수 생성 알고리즘을 실행하기 위해 쓰는 수
자연어 논문 추천
1. RoBERTa
https://arxiv.org/abs/1907.11692
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging. Training is computationally expensive, often done on private datasets of different sizes, and, as we will show, hyperpar
arxiv.org
2. BERT
https://arxiv.org/abs/1810.04805
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designed to pre-train deep bidirectional representations from unla
arxiv.org
3. Transformer
https://arxiv.org/abs/1706.03762
Attention Is All You Need
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and decoder through an attention mechanism. We propose a new
arxiv.org
4. GPT1
https://www.cs.ubc.ca/~amuham01/LING530/papers/radford2018improving.pdf
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