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RoBERTa-Clickbait-Detection
christinacdl/RoBERTa-Clickbait-Detection
RoBERTa-Clickbait-Detection is a text classification model from christinacdl. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Jan 21, 2024
- Updated
- Jan 21, 2024
- SHA
- d3afc634
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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. -->
RoBERTa-Clickbait-Detection
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1089
- Micro F1: 0.9847
- Macro F1: 0.9846
- Accuracy: 0.9847
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Framework versions
- Transformers 4.36.1
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jan 21, 2024
- Updated
- Jan 21, 2024