Update numbers in readme

README.md

@@ -708,13 +708,12 @@ configs:
 # 💾🏋️💾 DataBench 💾🏋️💾
 
 This repository contains the original 80 datasets used for the paper [Question Answering over Tabular Data with DataBench:
-A Large-Scale Empirical Evaluation of LLMs](https://huggingface.co/datasets/cardiffnlp/databench/resolve/main/Databench-LREC-Coling-2024.pdf) which appeared in LREC-COLING 2024.
+A Large-Scale Empirical Evaluation of LLMs](https://huggingface.co/datasets/cardiffnlp/databench/resolve/main/Databench-LREC-Coling-2024.pdf) which appeared in LREC-COLING 2024 and the associated SemEval 2025 Task 8 competition.
 
 Large Language Models (LLMs) are showing emerging abilities, and one of the latest recognized ones is tabular
 reasoning in question answering on tabular data. Although there are some available datasets to assess question
 answering systems on tabular data, they are not large and diverse enough to evaluate this new ability of LLMs.
-To this end, we provide a corpus of 65 real world datasets, with 3,269,975 and 1615 columns in total, and 1300 questions to evaluate your models for the task of QA over Tabular Data.
-
+To this end, we provide a corpus of 80 real-world datasets, comprising a total of 3,708,884 rows, 2,006 columns, and 1,822 questions to evaluate models for the task of question answering (QA) over tabular data.
 
 ## Usage