Update README.md

README.md

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     macro avg      0.92      0.87      0.88     47159
     weighted avg   0.91      0.89      0.88     47159
 
+The overall accuracy of the model was 89%, which is consistent with its previous results. For Class 0, the precision score was 100%, meaning it was able to predict every phishing website correctly. Its recall score was 74%, meaning it missed about 26% of actual phishing samples. For Class 1, its precision score was 84% and its recall score was 100%. This shows that the model leans toward predicting '1,' while favoring recall rather than precision.
+The model could possibly be used for real scenarios, but not for high risk use. It would be helpful in situations where you only need a general screening of phishing vs legitimate websites. So although it is accurate, it is not accurate enough. However, I would still trust this model. It performs well and behaves predictably. If more precision/recall is needed, then it would certainly make sense to use a more complex model. It all depends on what the model is being used for.
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 # Model Card Authors
 
 Anthony Martinez