diff --git a/aimodel/src/lib/ai/components/MetricSensitivity.py b/aimodel/src/lib/ai/components/MetricSensitivity.py
index 4060d7c..5d711f6 100644
--- a/aimodel/src/lib/ai/components/MetricSensitivity.py
+++ b/aimodel/src/lib/ai/components/MetricSensitivity.py
@@ -3,11 +3,10 @@ import math
 import tensorflow as tf
 
 def sensitivity(y_true, y_pred):
+	y_pred = tf.math.argmax(y_pred, axis=-1)
 	y_true = tf.cast(y_true, dtype=tf.float32)
 	y_pred = tf.cast(y_pred, dtype=tf.float32)
 	
-	y_pred = tf.math.argmax(y_pred, axis=-1)
-	
 	recall = tf.keras.metrics.Recall()
 	recall.update_state(y_true, y_pred)
 	return recall.result()
diff --git a/aimodel/src/lib/ai/components/MetricSpecificity.py b/aimodel/src/lib/ai/components/MetricSpecificity.py
index 60b4599..05bf156 100644
--- a/aimodel/src/lib/ai/components/MetricSpecificity.py
+++ b/aimodel/src/lib/ai/components/MetricSpecificity.py
@@ -13,11 +13,10 @@ def specificity(y_pred, y_true):
 	Returns:
 	Specificity score
 	"""
+	y_pred = tf.math.argmax(y_pred, axis=-1)
 	y_true = tf.cast(y_true, dtype=tf.float32)
 	y_pred = tf.cast(y_pred, dtype=tf.float32)
 	
-	y_pred = tf.math.argmax(y_pred, axis=-1)
-	
 	neg_y_true = 1 - y_true
 	neg_y_pred = 1 - y_pred
 	fp = K.sum(neg_y_true * y_pred)