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Add training_results.json

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  1. training_results.json +130 -0
training_results.json ADDED
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+ {
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+ "model": "TinyBert-CNN",
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+ "hyperparameters": {
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+ "batch_size": 16,
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+ "epochs": 20,
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+ "bert_lr": 2e-05,
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+ "head_lr": 0.001,
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+ "weight_decay": 0.01,
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+ "max_length": 128,
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+ "patience": 5,
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+ "label_smoothing": 0.1
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+ },
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+ "training_duration_seconds": 212.44,
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+ "epochs_trained": 7,
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+ "metrics": {
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+ "accuracy": 0.996,
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+ "f1_score": 0.996,
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+ "precision": 0.996,
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+ "recall": 0.996,
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+ "test_loss": 0.0691
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+ },
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+ "per_class_metrics": {
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+ "On-Topic Question": {
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+ "precision": 0.9934,
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+ "recall": 0.9967,
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+ "f1_score": 0.995,
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+ "support": 300
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+ },
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+ "Off-Topic Question": {
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+ "precision": 0.9967,
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+ "recall": 0.9933,
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+ "f1_score": 0.995,
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+ "support": 300
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+ },
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+ "Emotional-State": {
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+ "precision": 0.9934,
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+ "recall": 1.0,
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+ "f1_score": 0.9967,
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+ "support": 300
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+ },
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+ "Pace-Related": {
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+ "precision": 0.9967,
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+ "recall": 0.9933,
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+ "f1_score": 0.995,
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+ "support": 300
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+ },
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+ "Repeat/clarification": {
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+ "precision": 1.0,
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+ "recall": 0.9967,
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+ "f1_score": 0.9983,
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+ "support": 300
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+ }
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+ },
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+ "confusion_matrix": [
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+ ],
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+ "training_history": {
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+ "train_loss": [
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+ 1.0757,
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+ 0.5031,
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+ 0.4618,
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+ 0.4458,
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+ 0.4364,
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+ 0.4299,
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+ 0.4253
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+ ],
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+ "val_loss": [
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+ 0.1182,
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+ 0.055,
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+ 0.0643,
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+ 0.0578,
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+ 0.0628,
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+ 0.0615,
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+ 0.0599
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+ ],
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+ "val_acc": [
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+ 0.9853,
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+ 0.996,
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+ 0.9947,
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+ 0.9967,
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+ 0.9953,
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+ 0.9993,
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+ 0.998
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+ ],
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+ "val_f1": [
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+ 0.9853,
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+ 0.996,
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+ 0.9967,
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+ 0.9953,
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+ 0.9993,
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+ ]
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+ },
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+ "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"
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+ }