text-classification dataset:imdb license:apache-2.0 region:us
---
license: apache-2.0
datasets:
- imdb
metrics:
- accuracy
pipeline_tag: text-classification
---

# LSTM Text Classification Model for Sentiment Analysis

This repository contains a Long Short-Term Memory (LSTM) text classification model trained on the IMDB dataset for sentiment analysis. The model has achieved an accuracy of 96% on the test dataset and is available for use as a TensorFlow model.

## Model Details
- **Architecture**: Long Short-Term Memory (LSTM) Neural Network
- **Dataset**: IMDB Movie Reviews (Sentiment Classification)
- **Accuracy**: 96%

## Usage
You can use this model for sentiment analysis tasks. Below are some code snippets to help you get started:

```python
# Load the model and perform inference
import tensorflow as tf
model = tf.keras.models.load_model('imdb_lstm_model.h5')


# Perform inference
prediction = model.predict([text])

# Get the predicted sentiment (e.g., 'Positive' or 'Negative')
predicted_sentiment = "Positive" if prediction > 0.5 else "Negative"
