Update README.md

README.md

@@ -281,5 +281,80 @@ AEHGGLYYGMAPDGSICDDGKYHWVQAESMAAAAVLAVRTGDARYWQWYDRIWAYCWAHFVDHEHGAWFRILHRDNRNTT
 LWALDAPGFSKESRSAALGRP", "output": "5.3.1.7"}], "is_classification": false}
 ```
 
+## OPEval: Nine evaluation tasks using the OPI dataset
+
+To assess the effectiveness of instruction tuning with the OPI dataset, we developed OPEval, which comprises three categories of evaluation tasks. Each category includes three specific tasks. The table below outlines the task types, names, and the corresponding sizes of the training and testing sets.
+
+<table border="1" style="text-align:center; border-collapse:collapse;">
+  <tr>
+    <th style="text-align:center;">Task Type</th>
+    <th style="text-align:center;">Type Abbr.</th>
+    <th style="text-align:center;">Task Name</th>
+    <th style="text-align:center;">Task Abbr.</th>
+    <th style="text-align:center;">Training set size</th>
+    <th style="text-align:center;">Testing set size</th>
+  </tr>
+  <tr>
+    <td rowspan="3">Sequence Understanding</td>
+    <td rowspan="3">SU</td>
+    <td>EC Number Prediction</td>
+    <td>EC_number</td>
+    <td style="text-align:center;">74,487</td>
+    <td style="text-align:center;">392 (NEW-392), 149 (Price-149)</td>
+  </tr>
+  <tr>
+    <td>Fold Type Prediction</td>
+    <td>Fold_type</td>
+    <td style="text-align:center;">12,312</td>
+    <td style="text-align:center;">718 (Fold), 1254 (Superfamily), 1272 (Family)</td>
+  </tr>
+  <tr>
+    <td>Subcellular Localization Prediction</td>
+    <td>Subcellular_localization</td>
+    <td style="text-align:center;">11,230</td>
+    <td style="text-align:center;">2,772</td>
+  </tr>
+  <tr>
+    <td rowspan="3">Annotation Prediction</td>
+    <td rowspan="3">AP</td>
+    <td>Function Keywords Prediction</td>
+    <td>Keywords</td>
+    <td style="text-align:center;">451,618</td>
+    <td style="text-align:center;">184 (CASPSimilarSeq), 1,112 (IDFilterSeq), 4562 (UniprotSeq)</td>
+  </tr>
+  <tr>
+    <td>Gene Ontology(GO) Terms Prediction</td>
+    <td>GO</td>
+    <td style="text-align:center;">451,618</td>
+    <td style="text-align:center;">184 (CASPSimilarSeq), 1,112 (IDFilterSeq), 4562 (UniprotSeq)</td>
+  </tr>
+  <tr>
+    <td>Function Description Prediction</td>
+    <td>Function</td>
+    <td style="text-align:center;">451,618</td>
+    <td style="text-align:center;">184 (CASPSimilarSeq), 1,112 (IDFilterSeq), 4562 (UniprotSeq)</td>
+  </tr>
+  <tr>
+    <td rowspan="3">Knowledge Mining</td>
+    <td rowspan="3">KM</td>
+    <td>Tissue Location Prediction from Gene Symbol</td>
+    <td>gSymbol2Tissue</td>
+    <td style="text-align:center;">8,723</td>
+    <td style="text-align:center;">2,181</td>
+  </tr>
+  <tr>
+    <td>Cancer Prediction from Gene Symbol</td>
+    <td>gSymbol2Cancer</td>
+    <td style="text-align:center;">590</td>
+    <td style="text-align:center;">148</td>
+  </tr>
+  <tr>
+    <td>Cancer Prediction from Gene Name</td>
+    <td>gName2Cancer</td>
+    <td style="text-align:center;">590</td>
+    <td style="text-align:center;">148</td>
+  </tr>
+</table>
+
 ## License
 The dataset is licensed under a Creative Commons Attribution Non Commercial 4.0 License. The use of this dataset should also abide by the original [License & Disclaimer](https://www.uniprot.org/help/license) and [Privacy Notice](https://www.uniprot.org/help/privacy) of UniProt.