--- license: apache-2.0 language: - ru tags: - ner widget: - text: "628672, Автономный Округ Ханты-Мансийский Автономный Округ - Югра,, Г. Лангепас, Ул. Солнечная, Д.21" --- # address-ner-ru Address NER model to find address parts from string [https://huggingface.co/aidarmusin/address-ner-ru](https://huggingface.co/aidarmusin/address-ner-ru) # Dataset 5K raw addresses dataset 90% for training and 10% for evaluation # Evaluation | Metric | Value | | --- | --- | | eval_overall_precision | 0.9550486413955048 | | eval_overall_recall | 0.9644308943089431 | | eval_overall_f1 | 0.9597168380246082 | | eval_overall_accuracy | 0.9770456798596813 | | eval_Apartment_f1 | 0.9663865546218489 | | eval_Apartment_number | 352 | | eval_Building_precision | 0.8695652173913043 | | eval_Building_recall | 0.9195402298850575 | | eval_Building_f1 | 0.8938547486033519 | | eval_Building_number | 87 | | eval_Country_precision | 0.9950738916256158 | | eval_Country_recall | 0.9805825242718447 | | eval_Country_f1 | 0.9877750611246944 | | eval_Country_number | 206 | | eval_District_precision | 0.9562043795620438 | | eval_District_recall | 0.9924242424242424 | | eval_District_f1 | 0.9739776951672863 | | eval_District_number | 132 | | eval_House_precision | 0.9702380952380952 | | eval_House_recall | 0.9760479041916168 | | eval_House_f1 | 0.973134328358209 | | eval_House_number | 501 | | eval_Region_precision | 0.9826989619377162 | | eval_Region_recall | 0.9861111111111112 | | eval_Region_f1 | 0.9844020797227037 | | eval_Region_number | 288 | | eval_Settlement_precision | 0.9599271402550091 | | eval_Settlement_recall | 0.9547101449275363 | | eval_Settlement_f1 | 0.9573115349682106 | | eval_Settlement_number | 552 | | eval_Street_precision | 0.9424603174603174 | | eval_Street_recall | 0.9615384615384616 | | eval_Street_f1 | 0.9519038076152305 | | eval_Street_number | 494 | | eval_ZipCode_precision | 0.9208211143695014 | | eval_ZipCode_recall | 0.9235294117647059 | | eval_ZipCode_f1 | 0.9221732745961821 | | eval_ZipCode_number | 340 | # Example ```python from transformers import pipeline import torch import logging device = "cuda:0" if torch.cuda.is_available() else "cpu" logging.info(f"using device: {device}") address_ner_pipeline = pipeline("ner", model="aidarmusin/address-ner-ru", device=device) address = "628672,,,, Автономный Округ Ханты-Мансийский Автономный Округ - Югра,, Г. Лангепас, Ул. Солнечная, Д.21" entities = address_ner_pipeline(address) print(entities) ```