Omkar2118/datasets huggingface dataset:
FLoRes-101

FLoRes-101 is an evaluation benchmark for low-resource and multilingual machine translation. It consists of 3001 sentences extracted from English Wikipedia, covering a variety of different topics and domains. These sentences have been translated into 101 languages by professional translators through a carefully controlled process.

The FLoRes-101 dataset was introduced to address the lack of good evaluation benchmarks for low-resource languages. It enables better assessment of model quality in these languages and allows for the evaluation of many-to-many multilingual translation systems, as all translations are multilingually aligned.

Introducing paper: The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation