{
    "model": "TinyBert-CNN",
    "hyperparameters": {
        "batch_size": 16,
        "epochs": 20,
        "bert_lr": 2e-05,
        "head_lr": 0.001,
        "weight_decay": 0.01,
        "max_length": 128,
        "patience": 5,
        "label_smoothing": 0.1
    },
    "training_duration_seconds": 212.44,
    "epochs_trained": 7,
    "metrics": {
        "accuracy": 0.996,
        "f1_score": 0.996,
        "precision": 0.996,
        "recall": 0.996,
        "test_loss": 0.0691
    },
    "per_class_metrics": {
        "On-Topic Question": {
            "precision": 0.9934,
            "recall": 0.9967,
            "f1_score": 0.995,
            "support": 300
        },
        "Off-Topic Question": {
            "precision": 0.9967,
            "recall": 0.9933,
            "f1_score": 0.995,
            "support": 300
        },
        "Emotional-State": {
            "precision": 0.9934,
            "recall": 1.0,
            "f1_score": 0.9967,
            "support": 300
        },
        "Pace-Related": {
            "precision": 0.9967,
            "recall": 0.9933,
            "f1_score": 0.995,
            "support": 300
        },
        "Repeat/clarification": {
            "precision": 1.0,
            "recall": 0.9967,
            "f1_score": 0.9983,
            "support": 300
        }
    },
    "confusion_matrix": [
        [
            299,
            1,
            0,
            0,
            0
        ],
        [
            1,
            298,
            0,
            1,
            0
        ],
        [
            0,
            0,
            300,
            0,
            0
        ],
        [
            0,
            0,
            2,
            298,
            0
        ],
        [
            1,
            0,
            0,
            0,
            299
        ]
    ],
    "training_history": {
        "train_loss": [
            1.0757,
            0.5031,
            0.4618,
            0.4458,
            0.4364,
            0.4299,
            0.4253
        ],
        "val_loss": [
            0.1182,
            0.055,
            0.0643,
            0.0578,
            0.0628,
            0.0615,
            0.0599
        ],
        "val_acc": [
            0.9853,
            0.996,
            0.9947,
            0.9967,
            0.9953,
            0.9993,
            0.998
        ],
        "val_f1": [
            0.9853,
            0.996,
            0.9947,
            0.9967,
            0.9953,
            0.9993,
            0.998
        ]
    },
    "classification_report": "                      precision    recall  f1-score   support\n\n   On-Topic Question       0.99      1.00      1.00       300\n  Off-Topic Question       1.00      0.99      0.99       300\n     Emotional-State       0.99      1.00      1.00       300\n        Pace-Related       1.00      0.99      0.99       300\nRepeat/clarification       1.00      1.00      1.00       300\n\n            accuracy                           1.00      1500\n           macro avg       1.00      1.00      1.00      1500\n        weighted avg       1.00      1.00      1.00      1500\n"
}