# textattack /bert-base-uncased-rotten-tomatoes 0

## TextAttack Model Card

This bert-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 10 epochs with a batch size of 16, 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 0.875234521575985, as measured by the
eval set accuracy, found after 4 epochs.