Emotion-Aware-AI-Assistant/gemma3_12b-it-q4_K_M_hierarchical_results

该数据集包含与模型性能指标相关的特征，特别关注情感分类任务。特征包括各种准确度测量（宏观和加权）、不同情感（愤怒、厌恶、恐惧、快乐、中性、悲伤、惊讶）的F1分数、精确度、召回率、混淆矩阵详细信息、无效计数和响应时间指标。数据集在训练分割中似乎只有一个示例，提供了模型情感分类任务的详细性能指标。

The dataset contains features related to model performance metrics, with a particular focus on emotion classification tasks. Features include various accuracy measures (macro and weighted), F1 scores, precision, recall for different emotions (anger, disgust, fear, happiness, neutral, sadness, surprise), confusion matrix details, invalid counts, and response time metrics. The dataset appears to be a single example in the train split, providing detailed performance metrics for a models emotion classification task.