calpt's picture
Initial version.
- roberta
- adapter-transformers
- social_i_qa
- en
# Adapter `AdapterHub/roberta-base-pf-social_i_qa` for roberta-base
An [adapter]( for the `roberta-base` model that was trained on the [social_i_qa]( dataset and includes a prediction head for multiple choice.
This adapter was created for usage with the **[adapter-transformers](** library.
## Usage
First, install `adapter-transformers`:
pip install -U adapter-transformers
_Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. [More](
Now, the adapter can be loaded and activated like this:
from transformers import AutoModelWithHeads
model = AutoModelWithHeads.from_pretrained("roberta-base")
adapter_name = model.load_adapter("AdapterHub/roberta-base-pf-social_i_qa", source="hf")
model.active_adapters = adapter_name
## Architecture & Training
The training code for this adapter is available at
In particular, training configurations for all tasks can be found [here](
## Evaluation results
Refer to [the paper]( for more information on results.
## Citation
If you use this adapter, please cite our paper ["What to Pre-Train on? Efficient Intermediate Task Selection"](
title={What to Pre-Train on? Efficient Intermediate Task Selection},
author={Clifton Poth and Jonas Pfeiffer and Andreas Rücklé and Iryna Gurevych},
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "",
pages = "to appear",