Generate a new dataset with no author overlap between train and test splits

README.md

@@ -1,6 +1,6 @@
 HANOI challenge
 
-This challenge is based on the contents of the HANOI corpus described in detail below. This is a binary classification challenge: the aim is to classify interpreter notes as either being written by a trainee or a professional. The training split of the dataset consists of 988 training examples in the form of scans of interpreter notes, with 786 of them being made by professionals and 202 by trainees (university students during an interpreting course).
+This challenge is based on the contents of the HANOI corpus described in detail below. This is a binary classification challenge: the aim is to classify interpreter notes as either being written by a trainee or a professional. The training split of the dataset consists of 905 training examples in the form of scans of interpreter notes, with 744 of them being made by professionals and 160 by trainees (university students during an interpreting course).
 
 HANOI, or Handwritten Notation of Interpreters, is a corpus of handwritten notes for consecutive interpreting, collected from professional interpreters and interpreting students. It is the only resource of its kind in the world.