Training Log: IndoBERT + LSTM for Bot Detection
Epoch 1 (2025-06-04T07:59:01.187929)
Train Loss: 0.3595
Train Accuracy: 0.8321 | Precision: 0.8187 | Recall: 0.8543 | F1: 0.8361
Validation Accuracy: 0.8652 | Precision: 0.8858 | Recall: 0.8395 | F1: 0.8620
ROC AUC Score: 0.9501
Epoch 2 (2025-06-04T08:02:02.857571)
Train Loss: 0.3074
Train Accuracy: 0.8674 | Precision: 0.8754 | Recall: 0.8578 | F1: 0.8665
Validation Accuracy: 0.8812 | Precision: 0.8888 | Recall: 0.8724 | F1: 0.8805
ROC AUC Score: 0.9578
Epoch 3 (2025-06-04T08:05:04.187723)
Train Loss: 0.2900
Train Accuracy: 0.8702 | Precision: 0.8821 | Recall: 0.8557 | F1: 0.8687
Validation Accuracy: 0.8845 | Precision: 0.8971 | Recall: 0.8694 | F1: 0.8830
ROC AUC Score: 0.9617
Epoch 4 (2025-06-04T08:08:00.928979)
Train Loss: 0.2768
Train Accuracy: 0.8761 | Precision: 0.8880 | Recall: 0.8617 | F1: 0.8746
Validation Accuracy: 0.8838 | Precision: 0.8917 | Recall: 0.8744 | F1: 0.8830
ROC AUC Score: 0.9638
Epoch 5 (2025-06-04T08:10:55.293380)
Train Loss: 0.2659
Train Accuracy: 0.8825 | Precision: 0.8948 | Recall: 0.8678 | F1: 0.8811
Validation Accuracy: 0.8880 | Precision: 0.9028 | Recall: 0.8704 | F1: 0.8863
ROC AUC Score: 0.9653
Epoch 6 (2025-06-04T08:13:57.861897)
Train Loss: 0.2612
Train Accuracy: 0.8836 | Precision: 0.9011 | Recall: 0.8625 | F1: 0.8814
Validation Accuracy: 0.8890 | Precision: 0.8985 | Recall: 0.8779 | F1: 0.8880
ROC AUC Score: 0.9664
Epoch 7 (2025-06-04T08:17:00.986158)
Train Loss: 0.2577
Train Accuracy: 0.8866 | Precision: 0.8991 | Recall: 0.8716 | F1: 0.8851
Validation Accuracy: 0.8902 | Precision: 0.9057 | Recall: 0.8719 | F1: 0.8885
ROC AUC Score: 0.9670
Epoch 8 (2025-06-04T08:20:03.798388)
Train Loss: 0.2536
Train Accuracy: 0.8851 | Precision: 0.8981 | Recall: 0.8696 | F1: 0.8836
Validation Accuracy: 0.8910 | Precision: 0.8985 | Recall: 0.8824 | F1: 0.8903
ROC AUC Score: 0.9674
Epoch 9 (2025-06-04T08:23:06.184359)
Train Loss: 0.2473
Train Accuracy: 0.8888 | Precision: 0.9004 | Recall: 0.8750 | F1: 0.8875
Validation Accuracy: 0.8902 | Precision: 0.9032 | Recall: 0.8749 | F1: 0.8888
ROC AUC Score: 0.9680
Epoch 10 (2025-06-04T08:26:05.972908)
Train Loss: 0.2463
Train Accuracy: 0.8888 | Precision: 0.9005 | Recall: 0.8750 | F1: 0.8876
Validation Accuracy: 0.8942 | Precision: 0.9020 | Recall: 0.8853 | F1: 0.8936
ROC AUC Score: 0.9685
📷 Confusion Matrix
Confusion Matrix
