valurank/distilroberta-clickbait

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distilroberta-clickbait

This model is a fine-tuned version of distilroberta-base on a dataset of headlines. It achieves the following results on the evaluation set:

• —Loss: 0.0268
• —Acc: 0.9963

Training and evaluation data

The following data sources were used:

• —32k headlines classified as clickbait/not-clickbait from kaggle
• —A dataset of headlines from https://github.com/MotiBaadror/Clickbait-Detection

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 2e-05
• —trainbatchsize: 32
• —evalbatchsize: 32
• —seed: 12345
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_steps: 16
• —num_epochs: 20
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.11.3
• —Pytorch 1.10.1
• —Datasets 1.17.0
• —Tokenizers 0.10.3