textattack/distilbert-base-uncased-rotten-tomatoes

The model was fine-tuned for sequence classification using TextAttack and rotten_tomatoes . The best score the model achieved on this task was 0.8395872420262664, as measured by the eval set accuracy, found after 2 epochs . The model had a learning rate of 1e-05, a batch size of 128 and a maximum sequence length of 128 . For more information, check out [TextAttack on Github] and the model was trained with a cross-entropy loss function . For example, TextAttack was trained using the 'nlp' library, and the rotten tomatoes dataset was loaded using the TextAttack library. For example: TextAttack,