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License: MIT License
State of the Art Language models and Classifier for Marathi, which is spoken predominantly by Marathi people of Maharashtra, India
License: MIT License
The Marathi News Dataset contains only the Train and Validation Splits. This made it hard to report accuracy and compare to the baseline (which reports the validation accuracy). Hence, there's a need to have separate Train-Validation-Test sets.
Also, the headlines contain non-Devanagari characters (mostly English) and Arabic numerals. These need to be mapped to Devanagari characters and numerals. The original dataset contains ~50 duplicates which need to be cleaned.
Following the above steps, I have created new splits of the dataset (link here) which can be used for properly reporting scores on the Classification dataset.
Can it do lemmatization and stop words classification?
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