fixing binary prediction

app.py

@@ -32,10 +32,10 @@ def classify_text(text):
     with torch.no_grad():
         probabilities = torch.softmax(model(**inputs).logits, dim=1)[0]
 
-    human_prob = probabilities[24].item() * 100
     ai_probs = probabilities.clone()
     ai_probs[24] = 0
     ai_total_prob = ai_probs.sum().item() * 100
+    human_prob = 100 - ai_total_prob
 
     ai_argmax_index = torch.argmax(ai_probs).item()
     ai_argmax_model = label_mapping[ai_argmax_index]