Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Experimental Evaluation of Deep Learning models for Marathi Text
  Classification   The Marathi language is one of the prominent languages used in India. It is
predominantly spoken by the people of Maharashtra. Over the past decade, the
usage of language on online platforms has tremendously increased. However,
research on Natural Language Processing (NLP) approaches for Marathi text has
not received much attention. Marathi is a morphologically rich language and
uses a variant of the Devanagari script in the written form. This works aims to
provide a comprehensive overview of available resources and models for Marathi
text classification. We evaluate CNN, LSTM, ULMFiT, and BERT based models on
two publicly available Marathi text classification datasets and present a
comparative analysis. The pre-trained Marathi fast text word embeddings by
Facebook and IndicNLP are used in conjunction with word-based models. We show
that basic single layer models based on CNN and LSTM coupled with FastText
embeddings perform on par with the BERT based models on the available datasets.
We hope our paper aids focused research and experiments in the area of Marathi
NLP.

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The categories of this paper are: chem-ph
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The categories of this paper are: q-bio
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The categories of this paper are: funct-an
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The categories of this paper are: dg-ga
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The categories of this paper are: q-alg
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The categories of this paper are: math-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: nlin
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The categories of this paper are: q-fin
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The categories of this paper are: solv-int
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The categories of this paper are: hep-th
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The categories of this paper are: alg-geom
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The categories of this paper are: eess
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The categories of this paper are: ao-sci
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The categories of this paper are: cond-mat
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The categories of this paper are: bayes-an