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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
Sentiment AnalysisIMDB (test)
Accuracy45.2
248
Text ClassificationAG News (test)
Accuracy93.4
210
Text ClassificationYahoo! Answers (test)
Clean Accuracy72.3
133
Text ClassificationMR (test)
Accuracy76.24
99
Text ClassificationMR
Accuracy76.24
93
Topic ClassificationDBPedia (test)--
64
Text ClassificationR8 (test)
Accuracy96.1
56
Text ClassificationR8
Accuracy96.13
54
Document ClassificationOhsumed (test)
Accuracy57.7
54
Ontology ClassificationDBPedia (test)
Accuracy98.6
53
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