mistake during training

README.md

@@ -51,10 +51,10 @@ language:
 
 The classification task is split into two stages:
 1. URL features model
-    - **96.5%+ accuracy** on training and validation data
+    - **96.5%+ accurate** on training and validation data
     - 2,436,727 rows of labelled URLs
 2. Website features model
-    - **100.0% accuracy** on training and validation data
+    - **98.4% accurate** on training data, and **98.9% accurate** on validation data
     - 911,180 rows of 42 features
 
 ## Training Features
@@ -72,7 +72,7 @@ params = {
     'num_boost_round': [500, 750, 800, 900, 1000, 1250, 2000]
 }
 ```
-To reproduce the 100.0% accuracy model, you can follow the data analysis in the dataset page to filter out the unimportant features.
+To reproduce the 98.4% accurate model, you can follow the data analysis in the dataset page to filter out the unimportant features.
 Then train a LightGBM model using the most suited hyperparamters for this task:
 ```python
 params = {