In this lab, you build and evaluate various QA pipelines for financial documents.
The goal of this lab is to build a Question Answer (QA) pipeline for financial documents that financial analysts can use to inform their research by processing tons of text based data quickly, and pulling out key insights.
- Note your results may be different from the solutions. Evaluate your results.
Steps:
- Build an initial pipeline using a single text document
financial_context - Test a few pretrained models and select one to use for this task
- Evaluate the performance of your model
- Make recommendations for when if should and should not be used
- BONUS: Extend the pipeline to a larger set of documents from the FinQA data
| Topic | Description | Link |
|---|---|---|
| Lab | NLP Lap Notebook | Link |
| Data | FinQA | Link |
Before this activity, students should already be able to:
- Explore Hugging Face for NLP models
- Create an NLP pipeline in Hugging Face