DCSQE
Collection
For the 3 directions (ende, zhen, heen) covered in WMT2023, the model is pre-trained on top of XLMR-L using synthetic data generated by DCSQE.
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8 items
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Updated
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2
Using the DCSQE framework with the WMT2023 parallel corpus to generate synthetic data for pretraining a model, 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
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Model tree for DreamW1ngs/DCSQE-ende-syn
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FacebookAI/xlm-roberta-large