---
license: mit
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`.



# Download the Vectorizer model first and load the model :

# Usage :

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65dd9dc387458446d0a9da32/MlAfwDkAouKP5iWtzqHPj.png)