test_results.json

{
  "accuracy": 99.75490196078431,
  "precision": 99.61064243997404,
  "recall": 99.93489583333334,
  "f1": 99.77250568735782,
  "auc_roc": 0.9998845880681818,
  "average_precision": 0.9998977540703567,
  "confusion_matrix": [
    [
      1314,
      6
    ],
    [
      1,
      1535
    ]
  ],
  "classification_report": "              precision    recall  f1-score   support\n\n        Real     0.9992    0.9955    0.9973      1320\n        Fake     0.9961    0.9993    0.9977      1536\n\n    accuracy                         0.9975      2856\n   macro avg     0.9977    0.9974    0.9975      2856\nweighted avg     0.9976    0.9975    0.9975      2856\n"
}