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language: bn |
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# Bangla-Electra |
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This is a second attempt at a Bangla/Bengali language model trained with |
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Google Research's [ELECTRA](https://github.com/google-research/electra). |
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**As of 2022 I recommend Google's MuRIL model trained on English, Bangla, and other major Indian languages, both in their script and latinized script**: https://huggingface.co/google/muril-base-cased and https://huggingface.co/google/muril-large-cased |
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**For causal language models, I would suggest https://huggingface.co/sberbank-ai/mGPT, though this is a large model** |
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Tokenization and pre-training CoLab: https://colab.research.google.com/drive/1gpwHvXAnNQaqcu-YNx1kafEVxz07g2jL |
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V1 - 120,000 steps; V2 - 190,000 steps |
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## Classification |
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Classification with SimpleTransformers: https://colab.research.google.com/drive/1vltPI81atzRvlALv4eCvEB0KdFoEaCOb |
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On Soham Chatterjee's [news classification task](https://github.com/soham96/Bangla2Vec): |
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(Random: 16.7%, mBERT: 72.3%, Bangla-Electra: 82.3%) |
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Similar to mBERT on some tasks and configurations described in https://arxiv.org/abs/2004.07807 |
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## Question Answering |
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This model can be used for Question Answering - this notebook uses Bangla questions from Google's TyDi dataset: |
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https://colab.research.google.com/drive/1i6fidh2tItf_-IDkljMuaIGmEU6HT2Ar |
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## Corpus |
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Trained on a web crawl from https://oscar-corpus.com/ (deduped version, 5.8GB) and 1 July 2020 dump of bn.wikipedia.org (414MB) |
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## Vocabulary |
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Included as vocab.txt in the upload - vocab_size is 29898 |
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