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Tigrinya Q&A Benchmark (Question Answering)
Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.
The archive carries no text for this table; the description above is the archive's text for the task Question Answering. archive 2025-07-28
Results archive 2025-07-28
No rows in the archive for this table at snapshot 2025-07-28. It declares 2 metrics (Eval Loss, Perplexity) but no result was ever recorded against it. That says nothing about whether results exist elsewhere.
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