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visobert-clickbait-viclickbait-2025
bie-nhd/visobert-clickbait-viclickbait-2025
visobert-clickbait-viclickbait-2025 is a text classification model from bie-nhd. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jan 27, 2026
- Updated
- Jan 27, 2026
- SHA
- c0770817
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
visobert-clickbait-viclickbait-2025
This model is a fine-tuned version of uitnlp/visobert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5741
- Accuracy: 0.8333
- F1: 0.7299
- Precision: 0.7404
- Recall: 0.7196
- Auc Roc: 0.9031
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-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Auc Roc |
|---|---|---|---|---|---|---|---|---|
| 0.5653 | 1.0 | 96 | 0.4408 | 0.7778 | 0.5730 | 0.7183 | 0.4766 | 0.8527 |
| 0.3336 | 2.0 | 192 | 0.3896 | 0.8099 | 0.7005 | 0.6909 | 0.7103 | 0.8941 |
| 0.2028 | 3.0 | 288 | 0.4579 | 0.8246 | 0.7222 | 0.7156 | 0.7290 | 0.9005 |
| 0.0962 | 4.0 | 384 | 0.5741 | 0.8333 | 0.7299 | 0.7404 | 0.7196 | 0.9031 |
| 0.0344 | 5.0 | 480 | 0.6912 | 0.8275 | 0.7204 | 0.7308 | 0.7103 | 0.9021 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Jan 27, 2026
- Updated
- Jan 27, 2026