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README.md
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<h1>BERT-based Domain Classification for Japanese Complaint Texts</h1>
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<p>
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A BERT-based Japanese text classification model trained for
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domain classification of complaint texts.
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</p>
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<hr>
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<h2>Model Details</h2>
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<ul>
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<li>Architecture: BERT for Sequence Classification</li>
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<li>Language: Japanese</li>
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<li>Task: Multi-class domain classification</li>
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<li>Framework: Hugging Face Transformers</li>
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</ul>
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<hr>
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<h2>Training Data</h2>
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<p>
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Training corpus:
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</p>
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<p>
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<a href="https://huggingface.co/datasets/SHSK0118/BERT-basedDomainClassification_ComplaintTexts_ja">
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BERT-basedDomainClassification_ComplaintTexts_ja Dataset
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</a>
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</p>
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<p>
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Dataset split:
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</p>
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<ul>
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<li>Train: 90%</li>
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<li>Validation: 5%</li>
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<li>Test: 5%</li>
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</ul>
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<hr>
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<h2>Evaluation</h2>
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<p>
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Test Accuracy: <strong>73.0%</strong>
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</p>
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<hr>
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<h2>Performance Discussion</h2>
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<p>
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The model was trained on primarily formal written text (Wikimedia-derived corpus),
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while evaluation was conducted on complaint-style texts.
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</p>
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<p>
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The domain gap between formal and conversational language likely
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contributed to reduced performance.
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</p>
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<hr>
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<h2>Intended Use</h2>
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<ul>
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<li>Educational purposes</li>
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<li>Research prototyping</li>
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<li>Domain classification experiments</li>
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</ul>
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<hr>
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<h2>Limitations</h2>
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<ul>
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<li>No domain adaptation applied</li>
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<li>Performance sensitive to genre distribution</li>
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</ul>
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<hr>
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<h2>Author</h2>
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<p>
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Independent implementation by Shota Tokunaga.
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</p>
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