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Book Review Sentiment

Developed by mmcsweeney
A lightweight text sentiment analysis model based on DistilBERT, specifically fine-tuned for book review data
Downloads 20
Release Time : 2/12/2025

Model Overview

This model is a sentiment analysis model fine-tuned on DistilBERT-base-uncased, primarily used to analyze the sentiment tendency (positive/negative) of book review texts, achieving 92.84% accuracy on the evaluation set

Model Features

Efficient and Lightweight
Adopts the DistilBERT architecture, reducing model size by 40% compared to the original BERT while maintaining high accuracy
High Accuracy
Achieves 92.84% accuracy on book review sentiment analysis tasks
Fast Inference
The distilled architecture design enables faster model inference, suitable for production environment deployment

Model Capabilities

Text Sentiment Analysis
Natural Language Understanding
Short Text Classification

Use Cases

E-commerce
Online Book Review Analysis
Automatically analyze users' sentiment tendencies towards books
Accurately identifies over 92% of sentiment polarity
Market Research
Product Feedback Analysis
Batch process user evaluation data for publications
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