Runaway_advertisement_identifier

This is a SetFit model that can be used for text classification. The model is designed to identify runaway advertisements from early modern Danish newspapers. It was created from a sample of 4000 texts, of which half where runaway advertisements. It was created by Johan Heinsen and Sofus Landor Dam.

Base model: JohanHeinsen/Old_News_Segmentation_SBERT_V0.1

Metrics

Accuracy: 0.99333 F1: 0.99304

Get started like this:

from setfit import SetFitModel

model = SetFitModel.from_pretrained("JohanHeinsen/Runaway_advertisement_identifier_V1")

preds = model(["Min tjenstepige løb væk fra mig i nat", "Soldaten Jonas er forsvundet fra mit hus. Enhver bedes paagribe ham, om muligt. Han bærer en sort frakke.", "Jeg savner min hund."])

label_map = {0: "nej", 1: "ja"}

predicted_labels = [label_map[int(preds[0])], label_map[int(preds[1])]]

predicted_labels
Downloads last month
45
Safetensors
Model size
109M params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for JohanHeinsen/Runaway_advertisement_identifier_V1