textattack/albert-base-v2-rotten-tomatoes

Albert-base-v2 model was fine-tuned for sequence classification using TextAttack . The model was trained with a cross-entropy loss function . The best score the model achieved on this task was 0.8808630393996247, as measured by the eval set accuracy, found after 1 epoch . For more information, check out TextAttack on Github and the model is available on the site of the TextAttack Cardio . For example, the cardio is based on the rotten_tomatoes dataset, which was loaded using the nlp library and a batch size of 64 . The cardio has a learning rate of 2e-05 and a maximum sequence length,