docs(card): fix Model Description architecture mislabel and parameter count

README.md

@@ -11,7 +11,7 @@ pipeline_tag: fill-mask
 
 ## Model Description
 
-GPT-2 medium (345M parameters) foundation model pre-trained on compound SMILES strings from the MolCrawl dataset.
+BERT-medium foundation model (~306M parameters, 24-layer / 1024-hidden / 16-head topology, sized to match GPT-2-medium) pre-trained on compound SMILES strings from the MolCrawl dataset.
 
 The tokenizer is a character-level BPE tokenizer (vocab_size=612) that encodes each SMILES character as a separate token. Input SMILES strings should be passed **without** spaces (e.g. `CC(=O)O`). The `[SEP]` token (id=13) is used as the end-of-sequence marker.