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pretrained-language-models

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Identified ADEs and associated terms in an annotated corpus with Named Entity Recognition (NER) modeling with Flair and PyTorch. Fine-tuned pre-trained transformer models such as XLM-RoBERTa, SpanBERT, and Bio_ClinicalBERT. Achieved F1 scores of 0.73 and 0.77 for BIOES and BIO tagging models, respectively.

  • Updated Dec 20, 2024
  • Jupyter Notebook

This study focuses on political sentiment analysis during Bangladeshi elections, using the "Motamot" dataset to evaluate how Pre-trained Language Models (PLMs) and Large Language Models (LLMs) capture complex sentiment characteristics. The research explores the effectiveness of various models and learning strategies in understanding public opinion.

  • Updated Aug 10, 2024
  • Jupyter Notebook

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