Update README.md

README.md

@@ -10,6 +10,12 @@ pinned: false
 license: openrail
 ---
 
-The dataset used in the study "Uysal, A. K., Gunal, S., Ergin, S., & Gunal, E. S. (2013). The impact of feature extraction and selection on SMS spam filtering. Elektronika ir Elektrotechnika, 19(5), 67-72." is employed for training. The success ratios for Linear SVM Classifier is 0.9880 in terms of Macro-F1 when 10% of the dataset was used for testing. 
+ENGLISH
+The dataset used in the study "Uysal, A. K., Gunal, S., Ergin, S., & Gunal, E. S. (2013). The impact of feature extraction and selection on SMS spam filtering. Elektronika ir Elektrotechnika, 19(5), 67-72." is employed for training. The success ratio for Linear SVM Classifier is 0.9880 in terms of Macro-F1 when 10% of the dataset was used for testing. 
+The dataset is composed of SPAM and LEGITIMATE sms data.
+
+TÜRKÇE
+Bu çalışmada "Uysal, A. K., Gunal, S., Ergin, S., & Gunal, E. S. (2013). The impact of feature extraction and selection on SMS spam filtering. Elektronika ir Elektrotechnika, 19(5), 67-72." başlıklı çalışmadaki veri seti kullanılmıştır. Linear SVM sınıflandırıcı için başarı oranı, veri setinin %10'u test için kullanıldığında Makro-F1 açısından 0,9880'dir.
+Veri seti, SPAM ve LEGITIMATE kısa mesaj verilerinden oluşmaktadır.
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference