datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
spreadsheet-bench-v2-modified
SpreadsheetBench V2 Modified: Multi-Document QA
1,060 questions and reference answers grounded in 127 Excel workbooks, 35 PDFs and 9 DOCX files. This independent derivative of SpreadsheetBench 2 shifts the task from editing spreadsheets and producing workbook deliverables toward finding, interpreting and combining information in business documents.
An independent project built entirely from publicly available source material and newly authored QA annotations. No private company… See the full description on the dataset page: https://huggingface.co/datasets/hashmortar/spreadsheet-bench-v2-modified.sharc_modifiedShARC, a conversational QA task, requires a system to answer user questions based on rules expressed in natural language text. However, it is found that in the ShARC dataset there are multiple spurious patterns that could be exploited by neural models. SharcModified is a new dataset which reduces the patterns identified in the original dataset. To reduce the sensitivity of neural models, for each occurence of an instance conforming to any of the patterns, we automatically construct alternatives where we choose to either replace the current instance with an alternative instance which does not exhibit the pattern; or retain the original instance. The modified ShARC has two versions sharc-mod and history-shuffled. For morre details refer to Appendix A.3 .researchy_questions_modified
Dataset Summary
This dataset is derived from corbyrosset/researchy_questions, a collection of ~100k non-factoid, multi-perspective "Researchy Questions" mined from real Bing search engine logs. After a labor-intensive filtering funnel from billions of queries, these "needles in the haystack" are questions that probably require a lot of sub-questions and research to answer adequately, and are shown to be harder than other open-domain QA datasets like Natural Questions.… See the full description on the dataset page: https://huggingface.co/datasets/minorproject-research/researchy_questions_modified.distill_r1_110k_sft_modifiedBorrowed from https://huggingface.co/datasets/Congliu/Chinese-DeepSeek-R1-Distill-data-110k-SFT
Fix the <image> placeholder issue, which will cause error during training:
raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
squad_modified_2Modified_german_dpr_dataset
Original Dataset
The original dataset, deepset/germandpr, contains:
9275 training examples
1025 testing examples
Each example is a question/answer pair, consisting of:
One question
One answer
One positive context
Three negative contexts
You can find the original dataset here.
Modifications
Adding Easy Negative Examples
To enhance the dataset, an "easy negative example" was added to each row. The objective of this addition is to train the model to… See the full description on the dataset page: https://huggingface.co/datasets/AbrarHyder/Modified_german_dpr_dataset.