Update README.md

README.md

@@ -32,7 +32,7 @@ have a model that can predict binding residues from sequence alone. We also hope
 It has been shown that pLMs like ESM-2 contain structural information in the attention maps that recapitulate the contact maps of proteins, 
 and that single sequence masked language models like ESMFold can be used in atomically accurate predictions of folds, even outperforming 
 AlphaFold2. In our approach we show a positive correlation between scaling the model size and data 
-in a 1-to-1 fashion provides competative and possibly even SOTA performance, although our comparison to the SOTA models is not as fair and 
+in a 1-to-1 fashion provides competative and possibly even comparable to SOTA performance, although our comparison to the SOTA models is not as fair and 
 comprehensive as it could be (see [this report for more details](https://api.wandb.ai/links/amelie-schreiber-math/0asqd3hs) and also 
 [this repost](https://wandb.ai/amelie-schreiber-math/huggingface/reports/ESM-2-Binding-Sites-Predictor-Part-3-Scaling-Results--Vmlldzo1NDA3Nzcy?accessToken=npsm0tatgumcidfwxubzjyuhal512xu8sjmpnf11sebktjm9mheg69ja397q57ok)).