textattack/albert-base-v2-MRPC

Albert-base-v2 model was fine-tuned for sequence classification using TextAttack . The best score the model achieved on this task was 0.8970588235294118, as measured by the eval set accuracy, found after 4 epochs . The model was trained with a cross-entropy loss function and a learning rate of 2e-05, and a maximum sequence length of 128 . For more information, check out TextAttack on Github and the nlp library on the TextAttack website . For example, TextAttack has been updated with the latest version of TextAttack and the most recent version of this article has been published on the website. For more info,