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Document Classification System

BERT-based multilingual classifier achieving 94% accuracy on 10,000+ form entries, reducing manual processing time by 80%.

January 1, 2024
NLPTransformersPyTorchBERT

Overview

Developed a BERT-based classification system to automatically categorize form responses into discrete categories, significantly reducing manual administrative workload.

Technical Details

  • Model: Fine-tuned BERT for multilingual text classification
  • Dataset: 10,000+ multilingual form entries
  • Accuracy: 94% classification accuracy across multiple languages
  • Impact: Reduced manual processing time by 80% for administrative tasks

Pipeline

  1. Text preprocessing and multilingual tokenization
  2. Fine-tuned BERT encoder with classification head
  3. Batch inference pipeline for high-throughput processing
  4. Integration with existing administrative workflows

Technologies

Transformers, PyTorch, NLP preprocessing pipelines