textattack/bert-base-uncased-WNLI

The model was fine-tuned for sequence classification using TextAttack . It was trained with a cross-entropy loss function . The best score the model achieved on this task was 0.5633802816901409, as measured by the eval set accuracy, found after 1 epoch . For more information, check out TextAttack on Github and the nlp library on the TextAttack website . For example, the model was trained on a batch size of 64, a learning rate of 5e-05, and a maximum sequence length of 256. For example: The model achieved a score of 0.63380290101409 on the best score of this task .,