From 792395d47c86a9048642873761c58f9e32ca0567 Mon Sep 17 00:00:00 2001
From: TIANSHU ZHANG <814553853@qq.com>
Date: Tue, 21 Nov 2023 21:00:50 -0500
Subject: [PATCH] Update index.html
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Data Statistics
In-domain Evaluation
- We first evaluate TableLlama on 8 in-domain test sets. Due to the special semi-structured nature of tables, for most table-based tasks, existing work achieves SOTA results by using pretraining on large-scale tables and/or special model architecture design tailored for tables. Surprisingly, with a unified format and no extra special design, TableLlama can achieve comparable or even better performance on almost all the tasks. The table below shows the results:
+ We first evaluate TableLlama on 8 in-domain test sets. Due to the special semi-structured nature of tables, for most table-based tasks, existing work achieves SOTA results by using pretraining on large-scale tables and/or special model architecture design tailored for tables. Surprisingly, with a unified instruction tuning format without extra special design, TableLlama can achieve comparable or even better performance on almost all the tasks. The table below shows the results: