Update README.md

README.md

@@ -59,7 +59,7 @@ results = classifier("path/to/your_audio_file.wav")
 # {'score': 0.002027299487963319, 'label': 'noisy'}]
 print(results)
 ```
-
+> **Note:** The model outputs a confidence score for each label. In my use case, I consider audio to be *clean* if the score for the `clean` label is greater than **0.7**.
 ## Training Data
 
 This model was trained on a sophisticated, custom-built dataset of ~55,000 audio clips, specifically designed to teach the nuances of audio quality.