21 lines
1.2 KiB
Plaintext
21 lines
1.2 KiB
Plaintext
** DATASET for train
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1-passage score does not have to be 0,1. it can be a range from 0 to 1 (0,0.25,0.5,0.75,1) : we can get this core by llm and apply it in loss calculation.
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2-dataset needs preprocesing of removing negetive or positive passage by llm.
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3-miracle dataset: question = 2107 - passages = 21844 : some negetive passage can be related
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4-cross ligual dataset can be useful : query = first language - passage = second language
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5-swim-ir dataset : they have passage and they have created query from it : it is shit for persian
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6-parsinlu dataset: question = 600 - passage = 600 : all are positive
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7-persianqa dataset: question = 6306 - passage = less than queries : every passage has multiple queries : all are positive - be careful some query is impossible to anser
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8-pquad dataset :question = 48273 - passage = 10082 : every passage has multiple queries : be careful some query is impossible to anser : all are positive
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9-longragfa dataset: it is long doc and query and for evaluation : question = 250, passage = 1500 : not using
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10-Synthetic-persian-qa-retrieval dataset : question = 223423, passage = 250000 : negetaive passage are not exactly different : needs preprocessing |