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What is Evaluating Large Language Models Using Contrast Sets: An Experimental Approach about?
This study introduces a novel approach to evaluate Natural Language Inference (NLI) models using contrast sets, specifically applied to the Stanford Natural Language Inference (SNLI) dataset. The ELECTRA-small model demonstrated a significant drop in accuracy from 89.9% on the standard dataset to 72.5% on the contrast set, highlighting the need for improved model understanding of nuanced language. By fine-tuning the model with a contrast training dataset, accuracy on the contrast set improved to 85.5%, emph
- Author
- lucyzheng.rm
- Language
- EN