TextAttack Model Card
This cmarkea/distilcamembert-base model was fine-tuned using TextAttackand the allocine dataset loaded using the datasets library. The model was fine-tuned
for 1 epochs with a batch size of 16,
a maximum sequence length of 512, and an initial learning rate of 5e-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 0.9692, as measured by the
eval set accuracy, found after 1 epoch.
For more information, check out TextAttack on Github.