How to Fine-Tune an SLM for Emotion Recognition
English summary
This tutorial demonstrates how to fine-tune Mistral Small 3.1, a small language model, for emotion recognition. It focuses on handling imbalanced training sets and classifying 15 distinct emotions from social media posts. The guide provides Python code and practical steps to achieve this task. It is a hands-on approach for applying fine-tuning to real-world sentiment analysis.
Chinese summary
本教程演示如何微调小型语言模型Mistral Small 3.1以进行情绪识别。重点处理不平衡的训练集，并对社交媒体帖子中的15种不同情绪进行分类。指南提供了Python代码和实际操作步骤。这是一个将微调应用于实际情感分析的实践方法。
Key points
Fine-tune Mistral Small 3.1 for emotion classification
微调Mistral Small 3.1进行情绪分类
Handle imbalanced training datasets
处理不平衡的训练数据集
Classify 15 different emotions
分类15种不同情绪
Step-by-step Python tutorial
循序渐进Python教程
Practical application of SLM fine-tuning
SLM微调的实际应用