eval_detailed_metrics.json

{
  "confusion_matrix": [
    [
      95,
      11
    ],
    [
      0,
      194
    ]
  ],
  "classification_report": {
    "spoof": {
      "precision": 1.0,
      "recall": 0.8962264150943396,
      "f1-score": 0.945273631840796,
      "support": 106.0
    },
    "bona-fide": {
      "precision": 0.9463414634146341,
      "recall": 1.0,
      "f1-score": 0.9724310776942355,
      "support": 194.0
    },
    "accuracy": 0.9633333333333334,
    "macro avg": {
      "precision": 0.973170731707317,
      "recall": 0.9481132075471699,
      "f1-score": 0.9588523547675158,
      "support": 300.0
    },
    "weighted avg": {
      "precision": 0.9653008130081302,
      "recall": 0.9633333333333334,
      "f1-score": 0.9628354468260202,
      "support": 300.0
    }
  },
  "classification_report_str": "              precision    recall  f1-score   support\n\n       spoof     1.0000    0.8962    0.9453       106\n   bona-fide     0.9463    1.0000    0.9724       194\n\n    accuracy                         0.9633       300\n   macro avg     0.9732    0.9481    0.9589       300\nweighted avg     0.9653    0.9633    0.9628       300\n",
  "per_class_accuracy": {
    "spoof": 0.8962264150943396,
    "bona-fide": 1.0
  },
  "task": {
    "name": "Audio Classification",
    "type": "audio-classification"
  },
  "metrics": [
    {
      "name": "Accuracy",
      "type": "accuracy",
      "value": 0.9633333333333334
    }
  ]
}