README.md

---

license: cc-by-sa-3.0
language:
- ja
base_model:
- tohoku-nlp/bert-base-japanese
pipeline_tag: token-classification
tags:
- BERT
- Implicit-Subject
---

# Japanese Subject Insertion Model

<!-- Provide a quick summary of what the model is/does. -->

BERT based Token Classification model based on tohoku-nlp/bert-base-japanse and trained to predict in a Japanese sentence without an explicit subject where the subject would be.


## Model Uses


This model was trained as part of a bigger project to predict implicit subjects in Japanese text. You can find whole project here [https://github.com/Romi212/Japanese-Subject-Predictor-System] 



## Training Details

### Training Data

Model was trained using dataset https://github.com/UniversalDependencies/UD_Japanese-GSDLUW

The dataset was reduced only to sentences with a subject, and the subject was removed from the sentence saving the position to train the model to predict where the subject should go.