GitHub Issue Dataset

该数据集包含了用于预测问题标签的GitHub问题，并通过微调后的模型进行了处理。此外，该数据集在使用微调后的gpt-3.5-turbo模型进行评估时，取得了83.24%的精确度、82.87%的召回率和82.80%的F1分数。数据集的规模因仓库而异，其任务是预测GitHub问题的标签。

This dataset contains GitHub issues intended for tag prediction tasks, which have been processed using a fine-tuned model. Furthermore, when evaluated with the fine-tuned gpt-3.5-turbo model, this dataset achieved a precision of 83.24%, recall of 82.87%, and F1-score of 82.80%. The dataset's size varies across different repositories, and its core task is to predict tags for GitHub issues.