l3cube-pune/marathi-short-topic-bert-pruned-distill

Marathi-Short-Doc-Topic-BERT-Pruned

Marathi-Doc-Topic-BERT model is an l3cube-pune/marathi-topic-all-doc-v2 model pruned and distilled on Marathi documents from the L3Cube-IndicNews Corpus [dataset link]https://github.com/l3cube-pune/indic-nlp.
This dataset consists of sub-datasets like LDC (Long Document Classification), LPC (Long Paragraph Classification), and SHC (Short Headlines Classification), each having different document lengths.
This model is trained on the SHC dataset.

More details on the dataset, models, and baseline results can be found in our [paper]https://arxiv.org/abs/2401.02254

Citing:

@article{mirashi2024l3cube,
  title={L3Cube-IndicNews: News-based Short Text and Long Document Classification Datasets in Indic Languages},
  author={Mirashi, Aishwarya and Sonavane, Srushti and Lingayat, Purva and Padhiyar, Tejas and Joshi, Raviraj},
  journal={arXiv preprint arXiv:2401.02254},
  year={2024}
}

Other document topic models for different Indic languages are listed below:
Hindi-Doc-Topic-BERT
Bengali-Doc-Topic-BERT
Telugu-Doc-Topic-BERT
Tamil-Doc-Topic-BERT
Gujarati-Doc-Topic-BERT
Kannada-Doc-Topic-BERT
Odia-Doc-Topic-BERT
Malayalam-Doc-Topic-BERT
Punjabi-Doc-Topic-BERT