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Bert Base Multilingual Cased Nsmc
This is a checkpoint model fine-tuned on NSMC (Naver Sentiment Movie Corpus) based on bert-base-multilingual-cased, designed for sentiment analysis tasks.
Downloads 919
Release Time : 3/2/2022
Model Overview
This model is specifically optimized for sentiment analysis of Korean movie reviews, accurately determining positive or negative sentiment tendencies.
Model Features
Multilingual BERT foundation
Based on bert-base-multilingual-cased model, supporting multiple language processing
Movie review sentiment analysis
Fine-tuned specifically for Korean movie review data with high sentiment analysis accuracy
Easy to use
Can be directly called via Hugging Face's pipeline interface
Model Capabilities
Text sentiment analysis
Korean text processing
Positive/Negative sentiment classification
Use Cases
Film review analysis
Movie review sentiment classification
Automatically analyze whether user reviews of movies are positive or negative
Example shows 96.4% accuracy for negative reviews and 99.7% for positive reviews
Social media analysis
Social media sentiment monitoring
Analyze sentiment tendencies about movies or entertainment content on social media
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