I’m doing a project, on Google Colab, for fake news classification with LIAR dataset. I am running with three differents features extractors (TF-IDF, DistilBERT and LLAMA 2) and seven classifiers (Logistic Regression, SVM, Naive Bayes, KNN, Random Forest, AdaBoost and XGBoost). However, many tests gave the same result, even though they used different algorithms. Below, the values ​​found for the average accuracy entered are listed with the standard deviation in parentheses. The cells in orange are those that showed the same result (64.15 (2.22 x 10^-16)).