
The AMSunda dataset was introduced as the first resource designed explicitly for fine-tuning and evaluating embedding models in the Sundanese language. AMSunda dataset consists of two dataset types: (1) triplet data containing a query passage, a positive, and a negative response aimed for fine-tuning embedding models, and (2) BEIR-compatible data structured for evaluating embedding models on retrieval tasks.
Sundanese language, Sundanese dataset, Natural language processing, Text embedding, Information retrieval
Sundanese language, Sundanese dataset, Natural language processing, Text embedding, Information retrieval
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