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- W3121063397 abstract "In the last few years, deep learning has proved to be a very effective paradigm to discover patterns in large data sets. Unfortunately, deep learning training on small data sets is not the best option because most of the time traditional machine learning algorithms could get better scores. Now, we can train the neural network on a large data set then fine-tune on a smaller data set using the transfer learning technique. In this paper, we present our system for NADI shared Task: Country-level Dialect Identification, Our system is based on fine-tuning of BERT and it achieves 22.85 F1-score on Test Set and our rank is 5th out of 18 teams." @default.
- W3121063397 created "2021-01-18" @default.
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- W3121063397 date "2020-12-01" @default.
- W3121063397 modified "2023-09-24" @default.
- W3121063397 title "Arabic Dialect Identification Using BERT Fine-Tuning" @default.
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