christinacdl/clickbait_binary_detection_DeBERTa

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clickbaitbinarydetection_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
• —trainbatchsize: 4
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 8
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 10
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

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