---
license: apache-2.0
datasets:
- jakartaresearch/semeval-absa
language:
- en
metrics:
- f1
- exact_match
library_name: transformers
---


# Restaurant-T5-Base


The Restaurant-T5-Base model was introduced in [A Simple yet Effective Framework for Few-Shot Aspect-Based Sentiment Analysis (SIGIR'23)](https://doi.org/10.1145/3539618.3591940) by Zengzhi Wang, Qiming Xie, and Rui Xia.

The details are available at [Github:FS-ABSA](https://github.com/nustm/fs-absa) and [SIGIR'23 paper](https://doi.org/10.1145/3539618.3591940).


# Model Description

To bridge the domain gap between general pre-training and the task of interest in a specific domain (i.e., `restaurant` in this repo), we conducted *domain-adaptive pre-training*, 
continuing pre-training the language model (i.e., T5) on the unlabeled corpus of the domain of interest (i.e., `restaurant`) with the *text-infilling objective*
(corruption rate of 15% and average span length of 1).