Dataset Summary

The dataset contains 25000 Kotlin code samples selected from KStack dataset. The selection is performed based on the value of the code for learning algorithmic concepts in Kotlin.

Dataset Collection Procedure

The filtering is performed using zero-shot quality estimation based on Mistral-7B-Instruct-v0.2. The model is prompted to determine which of two files has higher "educational value for learning algorithms in Kotlin". The results of the comparisons are averaged and used to train a binary classifier based on CodeT5p-220m. The binary classifier is then applied to the entire KStack to obtain scores for each sample in the dataset. The log-probability of the classifier prediction used as a criterion of the selection.

Opt-out

If you want your data to be removed from dataset, or have any other questions, please reach out to Sergey Titov sergey.titov@jetbrains.com