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Applied Deep Learning 深度學習之應用 by Vivian Chen 陳縕儂 at NTU CSIE

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NTU-2022Fall-ADL

Applied Deep Learning 深度學習之應用 by Vivian Chen 陳縕儂

Surpassed strong baseline for all three assignments (Final grade: 100/100)

⭐Please consider starring this project if you find my code useful.⭐

Outline

For more details, refer to the reports.

  • HW1: Report
    • Intent Classification ← CNN+LSTM
      • Accuracy: 0.9027
    • Slot Tagging ← CNN+LSTM
      • Joint accuracy: 0.8060
  • HW2: Report
    • Chinese Question Answering with Multiple Paragraph
      • Divided into two stage inference
      • Paragraph Selection ← Chinese Macbert Large
        • Accuracy: 0.970
      • Chinese QA ← Chinese Macbert Large
        • Extact Match: 0.778
  • HW3: Report
    • Chinese News Summarization (Title Generation) ← mT5 base
      • Without RL finetuning:
        • Rouge 1: 0.2691
        • Rouge 2: 0.1081
        • Rouge 3: 0.2393
      • With policy gradient RL finetuning:
        • Rouge 1: 0.2712 (+0.8%)
        • Rouge 2: 0.1070 (-1.0%)
        • Rouge 3: 0.2411 (+0.8%)
  • Final Project:
    • Topic: MULTIMODAL PROMPT TUNING: REAL-WORLD USAGE ON NTU TREE CLASSIFICATION
    • Report
    • Presentation Slide
    • 10min Video
    • Achieved 85% accuracy under 8-shot setting with < 2min training time