FlippyDora/Qwen-1.5B-Instruct_amc23_8_orm_Qwen2.5-72B

该数据集包含四个主要特征：问题、输出、分数和标签。问题可能是指某种任务中提出的问题，输出是问题的响应或解答，分数可能是对输出的评估或置信度，标签可能代表输出分类或正确与否。训练集包含40个示例，整个数据集大小为662,680字节。数据集适用于机器学习模型的训练，尤其是那些涉及文本输入和输出处理、评估和分类的任务。

The dataset includes four main features: question, outputs, scores, and label. The question might refer to the queries proposed in some kind of task, outputs are the responses or answers to the questions, scores could be the evaluation or confidence of the outputs, and labels might represent the classification or correctness of the outputs. The training set contains 40 examples, and the entire dataset is 662,680 bytes in size. The dataset is suitable for training machine learning models, especially those involving text input and output processing, evaluation, and classification tasks.