Development of a RoBERTa-based NER Tool for Legal Contracts
Budget: $175 – $350 USD
Seeking a skilled AI Engineer to develop a Named Entity Recognition (NER tool using a RoBERTa model integrated with spaCy. The focus is on handling and preprocessing large volumes of PDF documents, setting up efficient data workflows, and training an NER model on around 300 annotated legal contract examples. Essential skills include proficiency in NLP, strong Python programming abilities, experience with OCR technology for older scans, and excellent communication skills for ongoing collaboration.
Budget: $250 - 350 USD
Type: Fixed Price
Duration: 1 month
Project Timeline:
1. Week 1: Migration of files from Dropbox to Google Drive.
2. Week 2: Data preprocessing and initiation of model training.
3. Weeks 3 & 4: Continued model training to achieve high F-score; final tests on broader dataset.
4. Conclusion: Complete project documentation and final model tuning.
Requirements:
Candidates must have demonstrated experience in AI, specifically NLP projects involving NER tools, and are expected to submit examples of past work related to this field.
Budget: $250 - 350 USD
Type: Fixed Price
Duration: 1 month
Project Timeline:
1. Week 1: Migration of files from Dropbox to Google Drive.
2. Week 2: Data preprocessing and initiation of model training.
3. Weeks 3 & 4: Continued model training to achieve high F-score; final tests on broader dataset.
4. Conclusion: Complete project documentation and final model tuning.
Requirements:
Candidates must have demonstrated experience in AI, specifically NLP projects involving NER tools, and are expected to submit examples of past work related to this field.