textattack/albert-base-v2-RTE

Albert-base-v2 model was fine-tuned for sequence classification using TextAttack . The best score the model achieved on this task was 0.776173285198556, as measured by the eval set accuracy, found after 4 epochs . The model was trained with a cross-entropy loss function and the glue dataset was loaded using the nlp library . For more information, check out TextAttack on Github and the TextAttack model is available at http://://www.textAttack.org//glues-loaded-to-the-measure-quality-search-ability-search/search-quality/textAttack-qualitySearch-qualitysearch-,