Re-host of the pre-cleaned ConvFinQA dataset distributed as part of Tomoro AI's "Applied AI Solution Engineer" take-home exercise. ConvFinQA itself is the conversational QA benchmark over single-page financial documents from Chen et al. (EMNLP 2022).
The data is a single JSON file with two splits, train (3,037 records) and dev (421 records). Each record carries:
id: stable per-record identifier
doc: a 10-K page split into pre_text, post_text, and a… See the full description on the dataset page:
https://huggingface.co/datasets/sharick008/convfinqa.
