---
license: mit
datasets:
- allocine
language:
- fr
tags:
- camembert
---
## 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 3 epochs with a batch size of 64,
    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 0.9707, as measured by the
eval set accuracy, found after 3 epochs.

For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack).