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roberta-base_vcom_questions
hilal-vcom/roberta-base_vcom_questions
roberta-base_vcom_questions is a text classification model from hilal-vcom. 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
- Jul 31, 2024
- Updated
- Sep 25, 2025
- SHA
- 569c7936
Try a prompt
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-base_vcom_questions
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0395
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1656 | 1.0 | 135 | 0.7632 |
| 0.432 | 2.0 | 270 | 0.2560 |
| 0.3726 | 3.0 | 405 | 0.4166 |
| 0.557 | 4.0 | 540 | 0.0973 |
| 0.0837 | 5.0 | 675 | 0.0395 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cpu
- Datasets 2.14.4
- Tokenizers 0.22.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jul 31, 2024
- Updated
- Sep 25, 2025