metadata
license: mit
language:
- en
- de
base_model:
- FacebookAI/xlm-roberta-large
pipeline_tag: translation
tags:
- quality_estimation
Spearman correlation coefficient is set as the best metric to train the sentence-level task.
Using the DCSQE framework, synthetic data is generated from the WMT2023 parallel corpus for pre-training, and then fine-tuned on the WMT2022 QE EN-DE training set, all implemented with the Fairseq framework.
For a detailed description of the DCSQE framework, please refer to the paper:
Alleviating Distribution Shift in Synthetic Data for Machine Translation Quality Estimation