arvine111/japanese-grammar-classification

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This model is a fine-tuned version of tohoku-nlp/bert-large-japanese-v2 designed to perform multi-class classification of Japanese grammar points. It was trained on labeled data sourced from the 日本語文型辞典 (grammar dictionary) and augmented with synthetic examples generated by a large language model.

Uses

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Direct Use

This model takes a Japanese sentence as input and predicts the most likely grammar point(s) used in that sentence. It can be integrated into language-learning applications, grammar checkers, or reading-assistant tools.

TOC

Out-of-Scope Use

• —Machine translation or text generation tasks.
• —Understanding semantics beyond grammar point identification.

Finetune Details

Finetune Data

Source: 日本語文型辞典 covering ~2400 grammar points. Augmentation: Synthetic sentences generated via a large language model to balance low-frequency grammar points (minimum 20 examples per point).

Finetune Procedure

• —Preprocessing: Tokenization with MeCab + Unidic lite; WordPiece subword encoding.
• —Batch size: 64
• —Max sequence length: 128 tokens
• —Optimizer: AdamW (learning rate = 3e-5, weight decay = 0.05)
• —Scheduler: Linear warmup of 20% steps, then linear decay
• —Epochs: 10
• —Mixed precision: Enabled (fp16)

Evaluation

• —Test set: Held-out sentences from dictionary and synthetic set (10% of total).
• —Metrics:
• —F1 Score (macro): 83.51%
• —Top2 F1 Score (macro): 94.96%