Update README.md

README.md

@@ -25,7 +25,12 @@ ProtBERT-PI is a fine-tuned sequence classification model built on ProtBERT (Ber
     Base model: Rostlab/prot_bert
     Pre-trained on large corpora of protein sequences using masked language modeling
 
-Fine-tuning was performed on a curated dataset of known protease inhibitors and non-protease inhibitor negative set. Sequences are tokenized by inserting spaces between amino acids (standard for ProtBERT), enabling effective representation learning. Maximum sequence length is configurable (default: 250 AA); longer sequences are truncated.
+Fine-tuning was performed on a curated dataset of known protease inhibitors and non-protease inhibitor negative set. 
+Sequences are tokenized by inserting spaces between amino acids (standard for ProtBERT), enabling effective representation learning. 
+Maximum sequence length is configurable (default: 250 AA); longer sequences are truncated.
+
+    Positive examples: known protease inhibitors (<250 AA) from the MEROPS database
+    Negative examples: non-inhibitors selected from UniProt using sequence similarity and Pfam domain analysis
 
 ---
 license: creativeml-openrail-m