This is a weakly supervised heuristic distillation model. The target is derived from TopLine Core features (ordlyd, singability, rhyme reuse, line length, section hints, stream normalization). It has not been trained on human accept/reject labels yet.

Use it as a first ranking signal for exploration, not as a final artistic judge.

Data

Source dataset: Larslouvre/topline-core-corpus
Danish songs: 247
Lines: 3062
Train/test split: grouped by song to avoid same-song leakage

Metrics

json

{
  "test_mae": 0.03193977245295291,
  "test_rmse": 0.03905283644419383,
  "test_r2": 0.8126409065765499,
  "test_spearman": 0.9022890369452443,
  "test_ndcg_at_20": 0.9593355974531179,
  "cv_mae_mean": 0.03411350540973291,
  "cv_mae_std": 0.0014743542672338325,
  "cv_rmse_mean": 0.040963221908164225,
  "cv_rmse_std": 0.0016030566426361575,
  "cv_r2_mean": 0.7070031835299886,
  "cv_r2_std": 0.01658186566627316,
  "n_lines": 3062,
  "n_songs": 247,
  "n_train_lines": 2145,
  "n_test_lines": 917,
  "n_train_songs": 197,
  "n_test_songs": 50,
  "target_mean": 0.581674631776957,
  "target_std": 0.08216859661908116,
  "trained_at": "2026-05-09T02:31:09.646660",
  "target_type": "weak_heuristic_distillation"
}

Usage

python

import joblib
import pandas as pd

model = joblib.load('model.joblib')
X = pd.DataFrame([{
    'line_text': 'jeg ser månen blive blokeret af dig',
    # include numeric feature columns from feature_columns.json
}])
score = model.predict(X)[0]

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Larslouvre/topline-hook-scorer-da-ridge

Danish Hook Quality Ridge Baseline

Important caveat

Data

Metrics

Usage

Generated by ML Intern

Larslouvre/
topline-hook-scorer-da-ridge