[P] XGBoost + TF-IDF for emotion prediction — good state accuracy but struggling with intensity (need advice)

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Hey everyone, I’m working on a small ML project (~1200 samples) where I’m trying to predict: Emotional state (classification — 6 classes) Intensity (1–5) of that emotion The dataset contains: journal_text (short, noisy reflections) metadata like: stress_level energy_level sleep_hours time_of_day previous_day_mood ambience_type face_emotion_hint duration_min reflection_quality 🔧 What I’ve done so far 1. Text processing Using TF-IDF: max_features = 500 → tried 1000+ as well ngram_range = (1,2) ...