Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Amharic News Text classification Dataset   In NLP, text classification is one of the primary problems we try to solve
and its uses in language analyses are indisputable. The lack of labeled
training data made it harder to do these tasks in low resource languages like
Amharic. The task of collecting, labeling, annotating, and making valuable this
kind of data will encourage junior researchers, schools, and machine learning
practitioners to implement existing classification models in their language. In
this short paper, we aim to introduce the Amharic text classification dataset
that consists of more than 50k news articles that were categorized into 6
classes. This dataset is made available with easy baseline performances to
encourage studies and better performance experiments.

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The categories of this paper are: gr-qc
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The categories of this paper are: hep-ex
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: funct-an
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The categories of this paper are: chem-ph
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The categories of this paper are: stat
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The categories of this paper are: eess
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The categories of this paper are: math
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The categories of this paper are: q-bio
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The categories of this paper are: bayes-an
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: astro-ph