Create README.md

README.md

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