TextAttack Model Card
This `bert` model was fine-tuned using TextAttack. The model was fine-tuned
for 5 epochs with a batch size of 8,
a maximum sequence length of 512, and an initial learning rate of 3e-05.
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 0.7342372881355932, as measured by the
eval set accuracy, found after 5 epochs.
For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack).
