I am looking for very specific help troubleshooting a binary BERT classifier for text (built using a HuggingFace model). My classifier takes as input a training set and a test set and outputs probabilities of belonging to each class for each observation. My problem is simple: I do not know how to match the predicted probabilities with the observations to which they correspond. The output of the prediction has slightly fewer rows than the number of observations in the corresponding dataset, so I think some NA values must be getting dropped, but I don't know how to find out which ones they are.
Ideally, the freelancer would take a look at the code and modify it so that when outputting probabilities, the code also outputs an additional column: the text that the probability was calculated from.
Bu iş için 10 freelancer ortalamada $166 teklif veriyor
Hi, I am Ibrahim, and I am a data scientist, transformers models tend to have some problems, as they are pretrained, what are you trying to predict with the bert model. Regards, Ibrahim Anjum
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