---
license: apache-2.0
datasets:
- openai/webgpt_comparisons
metrics:
- bleu
library_name: flair
pipeline_tag: zero-shot-image-classification
tags:
- chemistry
- biomedical
- finance
- legal
- science
- waifu-diffusion
- music
---
## TextAttack Model Card
This `albert-base-v2` model was fine-tuned for sequence classification using TextAttack 
and the glue dataset loaded using the `nlp` library. The model was fine-tuned 
for 5 epochs with a batch size of 32, 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 0.8970588235294118, as measured by the 
eval set accuracy, found after 4 epochs.

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