textattack/albert-base-v2-QQP

Albert-base-v2 model was fine-tuned for sequence classification using TextAttack . The best score the model achieved on this task was 0.9073707642839476, as measured by the eval set accuracy, found after 3 epochs . The model was trained with a cross-entropy loss function . For more information, check out TextAttack on Github and the nlp library on the TextAttack website . For example, TextAttack has a card with a card that says: "The card is the card of the card," and the card is "The Card of the Card with the Card of The Card" for the card, and it has a,