textattack/albert-base-v2-imdb

Albert-base-v2 model was fine-tuned for sequence classification using TextAttack . The best score the model achieved on this task was 0.89236, 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 card of a card with a card that says: "The card of the card is the card of TextAttack," and the card has an image of an image that says "the card is a card of The Card of the Card of,