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Bag of Tricks for Efficient Text Classification

About

This paper explores a simple and efficient baseline for text classification. Our experiments show that our fast text classifier fastText is often on par with deep learning classifiers in terms of accuracy, and many orders of magnitude faster for training and evaluation. We can train fastText on more than one billion words in less than ten minutes using a standard multicore~CPU, and classify half a million sentences among~312K classes in less than a minute.

Armand Joulin, Edouard Grave, Piotr Bojanowski, Tomas Mikolov• 2016

Related benchmarks

TaskDatasetResultRank
Text ClassificationAG News (test)
Accuracy93.4
326
Sentiment AnalysisIMDB (test)
Accuracy45.2
306
Topic ClassificationAG-News
Accuracy91.5
228
Text ClassificationMR
Accuracy76.24
174
Text ClassificationMR (test)
Accuracy76.24
164
Text ClassificationYahoo! Answers (test)
Clean Accuracy72.3
147
Text ClassificationDBpedia (DBP)
Accuracy98.1
131
Text ClassificationR8
Accuracy98.1
113
Text ClassificationR52
Accuracy94.74
98
Topic ClassificationDBPedia (test)--
64
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