---
language:
- ja
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
pipeline_tag: text-classification
datasets:
- LoneWolfgang/japanese-twitter-sentiment
---

# BERT for Sentiment Analysis of Japanese Twitter

This model was finetuned from [BERT for Japanese Twitter](https://huggingface.co/LoneWolfgang/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)](https://huggingface.co/datasets/LoneWolfgang/japanese-twitter-sentiment). 

For a model without the mixed label, please use the main version of [BERT for Japanese Twitter Sentiment](https://huggingface.co/LoneWolfgang/bert-for-japanese-twitter-sentiment).


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

## Example Pipeline
```python
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}]
```