I’m getting 61% accuracy on training model and 35% on testing model. I’ve passed all previous tests and the cost is correct after 2499 iterations.

Cost after iteration 0: 0.693049735659989

Cost after iteration 100: 0.6464320953428849

Cost after iteration 200: 0.6325140647912677

Cost after iteration 300: 0.6015024920354665

Cost after iteration 400: 0.5601966311605747

Cost after iteration 500: 0.5158304772764729

Cost after iteration 600: 0.4754901313943325

Cost after iteration 700: 0.43391631512257495

Cost after iteration 800: 0.4007977536203886

Cost after iteration 900: 0.3580705011323798

Cost after iteration 1000: 0.3394281538366413

Cost after iteration 1100: 0.30527536361962654

Cost after iteration 1200: 0.2749137728213015

Cost after iteration 1300: 0.2468176821061484

Cost after iteration 1400: 0.19850735037466102

Cost after iteration 1500: 0.17448318112556638

Cost after iteration 1600: 0.1708076297809692

Cost after iteration 1700: 0.11306524562164715

Cost after iteration 1800: 0.09629426845937156

Cost after iteration 1900: 0.0834261795972687

Cost after iteration 2000: 0.07439078704319085

Cost after iteration 2100: 0.06630748132267933

Cost after iteration 2200: 0.05919329501038172

Cost after iteration 2300: 0.053361403485605606

Cost after iteration 2400: 0.04855478562877019

Cost after iteration 2499: 0.04421498215868956

predictions_train = predict(train_x, train_y, parameters)

Accuracy: 0.6172248803827751

(Expected: Accuracy: 0.9999999999999998)

predictions_test = predict(test_x, test_y, parameters)

Accuracy: 0.36000000000000004

(Expected: Accuracy: 0.72)