Sentiment Analysis NLP Model
A deep learning model for classifying text sentiment as positive, negative, or neutral.
PROJECT DETAILS:
Client
Personal Project
DURATION
2 months
Year
2024
SUBJECT
SMM
I developed a sentiment analysis model to classify text data using PyTorch and TorchText. The model leverages preprocessed datasets and embeddings to predict sentiment with high accuracy. It includes real-time training monitoring with tqdm, performance visualization using matplotlib, and efficient data handling using NumPy. The solution can analyze reviews, tweets, and other text inputs, providing actionable insights for businesses and researchers.
- Achieved 92% accuracy on IMDB reviews dataset
- Efficient preprocessing and embedding handling
- Visualized training and validation metrics using matplotlib
- Reusable pipeline for multiple text datasets
Our Approach
- PyTorch
- NumPy
- TorchText
- Datasets
- Tqdm
- Matplotlib
“The model delivers fast and accurate sentiment predictions, making it very practical for analyzing large-scale text data.”