metadata

tags:
  - nlp
  - regression
  - tfidf
  - ridge
  - summaries
  - kaggle

🧠 CommonLit Summary Scoring Model

This model was trained using the CommonLit Evaluate Student Summaries dataset on Kaggle.
It predicts two scores for student-written summaries:

content → Idea coverage quality
wording → Clarity and phrasing quality

Built with:

TF-IDF vectorizer
Ridge Regression (scikit-learn)
MultiOutputRegressor wrapper

Example usage:

from joblib import load

model = load("ridge_model.pkl")
tfidf = load("tfidf_vectorizer.pkl")
summary = "This text discusses..."
X = tfidf.transform([summary])
pred = model.predict(X)