Natural Language Processing and Deep Learning
Skills Gained
Fine-Tuning BERT for Domain-Specific
Named Entity Recognition
Named Entity Recognition
Natural Language Processing (NLP)
BERT fine-tuning and model training
PyTorch framework
Named Entity Recognition (NER)
Data preprocessing and tokenization
Performance evaluation (F1 score, precision, recall)
BERT fine-tuning and model training
PyTorch framework
Named Entity Recognition (NER)
Data preprocessing and tokenization
Performance evaluation (F1 score, precision, recall)
2024
Our team fine-tuned pre-trained BERT model for Named Entity Recognition (NER) using data from J.R.R. Tolkien's Lord of the Rings universe. By adapting BERT with specialized datasets, we aimed to improve its accuracy in identifying domain-specific entities like characters, locations, and organizations. Training on both English Web Treebank and Lord of the Rings datasets led to significant performance improvements, demonstrating the value of incorporating domain-specific data.
Our team fine-tuned pre-trained BERT model for Named Entity Recognition (NER) using data from J.R.R. Tolkien's Lord of the Rings universe. By adapting BERT with specialized datasets, we aimed to improve its accuracy in identifying domain-specific entities like characters, locations, and organizations. Training on both English Web Treebank and Lord of the Rings datasets led to significant performance improvements, demonstrating the value of incorporating domain-specific data.