# textattack /albert-base-v2-rotten_tomatoes

## albert-base-v2 fine-tuned with TextAttack on the rotten_tomatoes dataset

This albert-base-v2 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 128, 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 0.8855534709193246, as measured by the
eval set accuracy, found after 1 epoch.


Mask token: [MASK]