How to Fine-Tune an SLM for Emotion Recognition
SMRTR summary
A fine-tuned small language model called MistralSmall-3.1.GoEmotions was built to detect 15 specific emotions in text, going beyond basic positive/negative sentiment. To handle heavily imbalanced training data, three techniques were combined — undersampling, synthetic data generation using ISMOTE, and focal loss weighting — achieving F1 scores above 0.7 for most target emotions.
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