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