--- license: mit datasets: - openbmb/RLAIF-V-Dataset language: - en metrics: - accuracy library_name: sklearn pipeline_tag: text-classification tags: - code --- ## Model Training The sentiment analysis model is trained using a Support Vector Machine (SVM) classifier with a linear kernel. The cleaned text data is transformed into a bag-of-words representation using the CountVectorizer. The trained model is saved as `Sentiment_classifier_model.joblib`, and the corresponding TF-IDF vectorizer is saved as `vectorizer_model.joblib`.