---
license: cc
language:
- ja
library_name: transformers
---

### Summary

This is a text classifier for assigning a [JLPT level](https://www.jlpt.jp/e/about/levelsummary.html). It was trained at the sentence level.
A pre-trained [cl-tohoku-bert-japanese-v3](https://huggingface.co/cl-tohoku/bert-base-japanese-v3) is finetuned on ~5000k labeled sentences obtained from language learning websites.
Performance on same distribution data is good.

```
              precision    recall  f1-score   support
          N5       0.62      0.66      0.64       145
          N4       0.34      0.36      0.35       143
          N3       0.33      0.67      0.45       197
          N2       0.26      0.20      0.23       192
          N1       0.59      0.08      0.15       202
    accuracy                           0.38       879
   macro avg       0.43      0.39      0.36       879
weighted avg       0.42      0.38      0.34       879
```

But on test data consisting of official JLPT material it is not so good. 

```
              precision    recall  f1-score   support
          N5       0.88      0.88      0.88        25
          N4       0.90      0.89      0.90        53
          N3       0.78      0.90      0.84        62
          N2       0.71      0.79      0.75        47
          N1       0.95      0.77      0.85        73
    accuracy                           0.84       260
   macro avg       0.84      0.84      0.84       260
weighted avg       0.85      0.84      0.84       260
```



Still, it can give a ballpark estimation of sentence difficulty, altough not very precise.