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Machine Translation · benchmark dataset · EN

The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation.

FLORES-101 is a high-quality, human-translated evaluation benchmark for low-resource and multilingual machine translation. It contains 3,001 sentences extracted from English Wikipedia and professionally translated into 101 languages through a carefully controlled process, producing a multilingually-aligned set useful for many-to-many MT evaluation. FLORES-101 was released to provide broad coverage of low-resource languages and to enable more reliable comparison of translation quality (commonly used as the dev/devtest evaluation benchmark). The dataset is distributed under a CC BY-SA 4.0 license.

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What a submission needs
  • 01A public checkpoint or API endpoint
  • 02A reproduction script with frozen commit + seed
  • 03Declared evaluation environment (Python, deps)
  • 04One row per metric declared by this dataset
  • 05A contact so we can follow up on discrepancies