https://galliard7.github.io/tags/nlp/Recent content in Nlp on Galliard7Hugoen-usMon, 15 Jan 2024 00:00:00 +0000https://galliard7.github.io/projects/pii-data-detection/Mon, 15 Jan 2024 00:00:00 +0000https://galliard7.github.io/projects/pii-data-detection/<h2 id="overview">Overview</h2> <p>Detecting personally identifiable information (PII) in student essays using named entity recognition. The challenge required identifying and classifying PII tokens across thousands of documents with high precision and recall.</p> <h2 id="approach">Approach</h2> <ul> <li><strong>Synthetic data generation</strong> to augment limited training data with realistic PII patterns</li> <li><strong>DeBERTa-based NER models</strong> fine-tuned for token-level PII classification</li> <li><strong>ONNX optimization</strong> for inference speed without sacrificing accuracy</li> <li><strong>Ensemble strategy</strong> combining multiple model checkpoints</li> </ul> <h2 id="result">Result</h2> <p>121/2048 🥉</p> <ul> <li><strong>Public leaderboard:</strong> 0.970</li> <li><strong>Private leaderboard:</strong> 0.956</li> </ul> <h2 id="links">Links</h2> <ul> <li><a href="https://github.com/Galliard7/pii-data-detection">GitHub Repository</a></li> </ul>https://galliard7.github.io/projects/llm-science-exam/Sun, 15 Oct 2023 00:00:00 +0000https://galliard7.github.io/projects/llm-science-exam/<h2 id="overview">Overview</h2> <p>Answering difficult science questions using large language models. The competition required selecting correct answers from multiple-choice science questions spanning physics, chemistry, biology, and other domains.</p> <h2 id="result">Result</h2> <p>194/2664 🥉</p> <h2 id="links">Links</h2> <ul> <li><a href="https://github.com/Galliard7/llm-science-exam">GitHub Repository</a></li> </ul>