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{
  "loss": 0.08122180355712771,
  "accuracy": 0.987012987012987,
  "macro_f1": 0.9850340136054422,
  "labels": [
    "data_integrity",
    "unrelated"
  ],
  "precision": [
    1.0,
    0.9811320754716981
  ],
  "recall": [
    0.96,
    1.0
  ],
  "f1": [
    0.9795918367346939,
    0.9904761904761905
  ],
  "support": [
    25,
    52
  ],
  "confusion_matrix": [
    [
      24,
      1
    ],
    [
      0,
      52
    ]
  ],
  "classification_report": "                precision    recall  f1-score   support\n\ndata_integrity       1.00      0.96      0.98        25\n     unrelated       0.98      1.00      0.99        52\n\n      accuracy                           0.99        77\n     macro avg       0.99      0.98      0.99        77\n  weighted avg       0.99      0.99      0.99        77\n"
}

	{
	"loss": 0.08122180355712771,
	"accuracy": 0.987012987012987,
	"macro_f1": 0.9850340136054422,
	"labels": [
	"data_integrity",
	"unrelated"
	],
	"precision": [
	1.0,
	0.9811320754716981
	],
	"recall": [
	0.96,
	1.0
	],
	"f1": [
	0.9795918367346939,
	0.9904761904761905
	],
	"support": [
	25,
	52
	],
	"confusion_matrix": [
	[
	24,
	1
	],
	[
	0,
	52
	]
	],
	"classification_report": " precision recall f1-score support\n\ndata_integrity 1.00 0.96 0.98 25\n unrelated 0.98 1.00 0.99 52\n\n accuracy 0.99 77\n macro avg 0.99 0.98 0.99 77\n weighted avg 0.99 0.99 0.99 77\n"
	}