# 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](https://github.com/QData/TextAttack).