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deberta-v3-base-mnli-finetuned-factcheck
iota-10/deberta-v3-base-mnli-finetuned-factcheck
deberta-v3-base-mnli-finetuned-factcheck is a text classification model from iota-10. 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
- deberta-v2
- Access
- Public
- Created
- Sep 13, 2025
- Updated
- Sep 13, 2025
- SHA
- 13dbfcce
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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. -->
deberta-v3-base-mnli-finetuned-factcheck
This model is a fine-tuned version of MoritzLaurer/DeBERTa-v3-base-mnli on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1057
- Accuracy: 0.98
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1089 | 1.0 | 732 | 0.0797 | 0.9808 |
| 0.0495 | 2.0 | 1464 | 0.0908 | 0.9823 |
| 0.0128 | 3.0 | 2196 | 0.1057 | 0.98 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- Created
- Sep 13, 2025
- Updated
- Sep 13, 2025