textattack/distilbert-base-uncased-ag-news

TextAttack Model CardThis distilbert-base-uncased model was fine-tuned for sequence classification using TextAttack

and the ag_news dataset loaded using the nlp library. The model was fine-tuned for 5 epochs with a batch size of 32, a learning rate of 2e-05, and a maximum sequence length of 128. Since this was a classification task, the model was trained with a cross-entropy loss function. The best score the model achieved on this task was 0.9478947368421052, as measured by the eval set accuracy, found after 1 epoch.

For more information, check out TextAttack on Github.