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---
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 finetuning, omitting the mixed examples.
## Labels
0 -> Negative;
1 -> Neutral;
2 -> Positive
## Example Pipeline
```python
from transformers import pipeline
sentiment = pipeline("sentiment-analysis", model="LoneWolfgang/bert-for-japanese-twitter-sentiment")
sentiment ("こちらのカフェ、サービスが残念でした。二度と行かないかな…😞 #がっかり")
```
```
[{'label': 'negative', 'score': 0.8242}]
```
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