Turkish Named Entity Recognition (NER) Model This model is the fine tuned model of "dbmdz/bert base turkish cased" using a reviewed version of well known Turkish NER dataset (https://github.com/stefan it/turkish bert/files/4558187/nerdata.txt). Fine tuning parameters: How to use: Pls refer "https://huggingface.co/transformers/ modules/transformers/pipelines/token classification.html" for entity grouping with aggregation strategy parameter. Reference test results: accuracy: 0.9933935699477056 f1: 0.9592969472710453 precision: 0.9543530277931161 recall: 0.9642923563325274 Evaluation results with the test sets proposed in "Küçük, D., Küçük, D., Arıcı, N. 2016. Türkçe Varlık İsmi Tanıma için bir Veri Kümesi ("A Named Entity Recognition Dataset for Turkish"). IEEE Sinyal İşleme, İletişim ve Uygulamaları Kurultayı. Zonguldak, Türkiye." paper. Test Set Acc. Prec. Rec. F1 Score 20010000 0.9946 0.9871 0.9463 0.9662 20020000 0.9928 0.9134 0.9206 0.9170 20030000 0.9942 0.9814 0.9186 0.9489 20040000 0.9943 0.9660 0.9522 0.9590 20050000 0.9971 0.9539 0.9932 0.9732 20060000 0.9993 0.9942 0.9942 0.9942 20070000 0.9970 0.9806 0.9439 0.9619 20080000 0.9988 0.9821 0.9649 0.9735 20090000 0.9977 0.989…
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