| ---
|
| license: cc-by-sa-3.0
|
| language:
|
| - ja
|
| base_model:
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| - 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. |
