clickbait_binary_detection_DeBERTa

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clickbait_binary_detection_DeBERTa

This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.7269
• Macro F1: 0.9010
• Micro F1: 0.9069
• Accuracy: 0.9069

Performance on test set:

• Accuracy: 0.911986301369863

• F1 score: 0.9053903329555788

• Precision: 0.9069346899004087

• Recall : 0.9039394560612273

• Matthews Correlation Coefficient: 0.8108686139956713

• Precision of each class: [0.92560647 0.88826291]

• Recall of each class: [0.93518519 0.87269373]

• F1 score of each class: [0.93037117 0.88040949]

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-06
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.27.1
• Pytorch 2.0.1+cu118
• Datasets 2.9.0
• Tokenizers 0.13.3