bot-detection-mbert

IndoBERT-GRU for Bot Detection on Platform X

This model uses MBERT to classify Twitter/X accounts as bots or humans based on their textual content and numeric features.

Model Architecture

• Base Model: bert-base-multilingual-cased
• Classifier: 2-layer feedforward with ReLU + Sigmoid

Dataset

The dataset includes Indonesian tweets with labels (0 for human, 1 for bot), along with additional numeric features such as favorite_count, retweet_count, reply_count, and quote_count.

Training Details

• Loss Function: Binary Cross Entropy (BCELoss)
• Optimizer: AdamW (lr = 2e-5)
• Epochs: 10
• Max Token Length: 128
• Batch Size: 16

Training Log

Evaluation Results

Final Validation Accuracy: 0.9370

Final Precision: 0.9333 Final Recall: 0.9408 Final F1-score: 0.9370

Confusion Matrix

Training Phase

Classification Report

              precision    recall  f1-score   support

         0.0       0.94      0.93      0.94      2008
         1.0       0.93      0.94      0.94      1992

    accuracy                           0.94      4000
   macro avg       0.94      0.94      0.94      4000
weighted avg       0.94      0.94      0.94      4000