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Bert_Model

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Bert_Model
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{
    "model_name": "DistilBERT Email Spam Detector",
    "model_architecture": "distilbert-base-uncased",
    "num_parameters": "~66 million",
    "task": "Binary Text Classification (Spam/Ham)",
    "training_config": {
        "num_epochs": 1,
        "batch_size": 16,
        "learning_rate": 5e-05,
        "max_sequence_length": 128,
        "optimizer": "Adam",
        "device": "cpu",
        "random_seed": 123
    },
    "dataset_info": {
        "total_samples": 5572,
        "train_samples": 3342,
        "val_samples": 1115,
        "test_samples": 1115,
        "spam_ratio": 0.13406317300789664
    },
    "training_metrics": {
        "final_train_loss": 0.07536028913482934,
        "final_train_accuracy": 99.37163543701172,
        "final_val_accuracy": 98.74439239501953,
        "total_training_time_minutes": 15.142122399806976
    },
    "test_metrics": {
        "area_under_pr_curve": 0.9950947543061519,
        "tpr_recall_sensitivity": 0.9395973154362416,
        "precision": 1.0,
        "f1_score": 0.9688581314878892,
        "tnr_specificity": 1.0,
        "npv": 0.9907692307692307,
        "fpr": 0.0,
        "fnr": 0.06040268456375839,
        "mcc": 0.9648440855638797,
        "accuracy": 0.9919282511210762
    },
    "confusion_matrix": {
        "true_negatives": 966,
        "false_positives": 0,
        "false_negatives": 9,
        "true_positives": 140
    },
    "training_history": {
        "train_loss": [
            0.07536028913482934
        ],
        "train_acc": [
            99.37163543701172
        ],
        "val_acc": [
            98.74439239501953
        ],
        "epoch_times": [
            908.5263459682465
        ]
    }
}