textattack/distilbert-base-uncased-rotten-tomatoes

TextAttack Model Card

This distilbert-base-uncased model was fine-tuned for sequence classificationusing TextAttack and the rotten_tomatoes dataset loaded using the nlp library. The model was fine-tuned for 3 epochs with a batch size of 128, a learning rate of 1e-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 0.8395872420262664, as measured by the eval set accuracy, found after 2 epochs.

For more information, check out TextAttack on Github.