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The monolingual Hindi BERT models currently available on the model hub do notperform better than the multi-lingual models on downstream tasks. We presentL3Cube-HindBERT, a Hindi BERT model pre-trained on Hindi monolingual corpus.Further, since Indic languages, Hindi and Marathi share the Devanagari script,we train a single model for both languages. We release DevBERT, a DevanagariBERT model trained on both Marathi and Hindi monolingual datasets. We evaluatethese models on downstream Hindi and Marathi text classification and namedentity recognition tasks. The HindBERT and DevBERT-based models showsignificant improvements over multi-lingual MuRIL, IndicBERT, and XLM-R. Basedon these observations we also release monolingual BERT models for other Indiclanguages Kannada, Telugu, Malayalam, Tamil, Gujarati, Assamese, Odia, Bengali,and Punjabi. These models are shared at https://huggingface.co/l3cube-pune .

L3Cube-HindBERT and DevBERT: Pre-Trained BERT Transformer models for Devanagari based Hindi and Marathi Languages