Sane words early s2

solution2.py

@@ -85,8 +85,8 @@ for i in range(80):
         #print(str(i), " ; ", cost)
         if (cost.item() < 40000):
             learning_rate = torch.tensor(0.00001, dtype=torch.float)
-        #if (cost.item() < 1614):
-        #    learning_rate = torch.tensor(0.000001, dtype=torch.float)
+        if (cost.item() < 1700):
+            learning_rate = torch.tensor(0.000001, dtype=torch.float)
         with torch.no_grad():
             W1 = W1 - learning_rate * W1.grad
             b1 = b1 - learning_rate * b1.grad
@@ -96,8 +96,9 @@ for i in range(80):
             dev_y_test = model(dev_x)
             dev_y_test_f = dev_y_test.numpy()
             dev_y_test = np.where(dev_y_test_f > 0.5, 1, 0)
-            print(dev_y_test)
-            score = f1_score(dev_y_test, dev_y_pred)
+            #print(dev_y_test)
+            recall = recall_score(dev_y_test, dev_y_pred, average='micro')
+            F1  = f1_score(dev_y_test, dev_y_pred)
 
 
         W1.requires_grad_(True)
@@ -105,15 +106,15 @@ for i in range(80):
         W2.requires_grad_(True)
         b2.requires_grad_(True)
 
-        if (score < 0.35):
+        if ((F1 > 0.3) & (F1<0.7)):
             break
 
-
-
-    print(score)
-    print(str(i), " ; ", cost)
+    print(dev_y_test)
+    print(F1, recall )
     print(str(i), " ; ", cost)
 
+    if ((F1 > 0.3) & (F1<0.7)):
+        break