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DutchMedicalTextDetector_v1_HEADONLY

Text Classification

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UMCU commited on Jul 17

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-We used GPT4.1-nano to classify generic texts from OSCAR as medical/non-medical. We labeled 400.000 texts, with about 40.000 labeled as positive.
 We then trained a SequenceClassifier on 80.000 samples with a 50/50 class ratio.

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+We used GPT4.1-nano to classify generic texts from OSCAR as non-medical/medical. We labeled 400.000 texts, with about 40.000 labeled as positive.
 We then trained a SequenceClassifier on 80.000 samples with a 50/50 class ratio.