metadata
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.