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{
  "loss": 0.36825408905537593,
  "accuracy": 0.897196261682243,
  "macro_f1": 0.8958867757629367,
  "labels": [
    "authentication_identity",
    "unrelated"
  ],
  "precision": [
    0.8076923076923077,
    0.9818181818181818
  ],
  "recall": [
    0.9767441860465116,
    0.84375
  ],
  "f1": [
    0.8842105263157894,
    0.907563025210084
  ],
  "support": [
    43,
    64
  ],
  "confusion_matrix": [
    [
      42,
      1
    ],
    [
      10,
      54
    ]
  ],
  "classification_report": "                         precision    recall  f1-score   support\n\nauthentication_identity       0.81      0.98      0.88        43\n              unrelated       0.98      0.84      0.91        64\n\n               accuracy                           0.90       107\n              macro avg       0.89      0.91      0.90       107\n           weighted avg       0.91      0.90      0.90       107\n"
}

	{
	"loss": 0.36825408905537593,
	"accuracy": 0.897196261682243,
	"macro_f1": 0.8958867757629367,
	"labels": [
	"authentication_identity",
	"unrelated"
	],
	"precision": [
	0.8076923076923077,
	0.9818181818181818
	],
	"recall": [
	0.9767441860465116,
	0.84375
	],
	"f1": [
	0.8842105263157894,
	0.907563025210084
	],
	"support": [
	43,
	64
	],
	"confusion_matrix": [
	[
	42,
	1
	],
	[
	10,
	54
	]
	],
	"classification_report": " precision recall f1-score support\n\nauthentication_identity 0.81 0.98 0.88 43\n unrelated 0.98 0.84 0.91 64\n\n accuracy 0.90 107\n macro avg 0.89 0.91 0.90 107\n weighted avg 0.91 0.90 0.90 107\n"
	}