BERT for Sentiment Analysis of Japanese Twitter

This model was finetuned from BERT for Japanese Twitter, which was adapted from Japanese BERT by Tohoku NLP by continuing MLM on a Twitter corpus.

It used Japanese Twitter Sentiment 1k (JTS1k).

For a model without the mixed label, please use the main version of BERT for Japanese Twitter Sentiment.

Labels

0 -> Negative; 1 -> Neutral; 2 -> Positive; 3 -> Mixed

Example Pipeline

from transformers import pipeline
sentiment = pipeline("sentiment-analysis", model="LoneWolfgang/bert-for-japanese-twitter-sentiment-mixed-label")
sentiment ("ケーキは美味しかったけど、店員さんの態度が少し残念だった。")

[{'label': 'mixed', 'score': 0.6090}]