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Sentiment Analysis On Yelp Fine Grained

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Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	Error	Paper Title	Repository
ULMFiT	29.98	Universal Language Model Fine-tuning for Text Classification
BERT_base+ITPT	29.42	How to Fine-Tune BERT for Text Classification?
DNC+CUW	34.40	Learning to Remember More with Less Memorization
BERT_large+ITPT	28.62	How to Fine-Tune BERT for Text Classification?
XLNet	27.05	XLNet: Generalized Autoregressive Pretraining for Language Understanding
SVDCNN	46.80	Squeezed Very Deep Convolutional Neural Networks for Text Classification
BiLSTM generalized pooling	33.45	Enhancing Sentence Embedding with Generalized Pooling
CCCapsNet	34.15	Compositional Coding Capsule Network with K-Means Routing for Text Classification
Char-level CNN	37.95	Character-level Convolutional Networks for Text Classification
SWEM-hier	36.21	Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms
DRNN	30.85	Disconnected Recurrent Neural Networks for Text Categorization	-
BERT large finetune UDA	32.08	Unsupervised Data Augmentation for Consistency Training
BERT large	29.32	Unsupervised Data Augmentation for Consistency Training
LEAM	35.91	Joint Embedding of Words and Labels for Text Classification
CNN	32.39	Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings	-
FastText	36.1	Bag of Tricks for Efficient Text Classification
DPCNN	30.58	Deep Pyramid Convolutional Neural Networks for Text Categorization

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