Fixes

app.py

@@ -126,7 +126,8 @@ def predict_genus(method: str, dna_sequence: str, latitude: str, longitude: str)
     if method == "fine_tuned_model":
         bert_inputs = tokenize(dna_sequence)
         logits = classification_model(bert_inputs, torch.zeros(1, 7))
-        probs = torch.softmax(logits, dim=1).squeeze()
+        temperature = 0.5
+        probs = torch.softmax(logits / temperature, dim=1).squeeze()
         top_k = torch.topk(probs, 10)
         top_k = pd.Series(
             top_k.values.detach().numpy(),
@@ -136,10 +137,12 @@ def predict_genus(method: str, dna_sequence: str, latitude: str, longitude: str)
 
     fig, ax = plt.subplots()
     ax.bar(top_k.index.astype(str), top_k.values)
+    ax.set_ylim(0, 1)
     ax.set_title("Genus Prediction")
     ax.set_xlabel("Genus")
     ax.set_ylabel("Probability")
-    ax.set_xticklabels(top_k.index.astype(str), rotation=90) 
+    ax.set_xticklabels(top_k.index.astype(str), rotation=90)
+    fig.subplots_adjust(bottom=0.3)
     fig.canvas.draw()
 
     return PIL.Image.frombytes("RGB", fig.canvas.get_width_height(), fig.canvas.tostring_rgb())