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xlm-roberta-base-finetuned-PersianQuAD
Z-Jafari/xlm-roberta-base-finetuned-PersianQuAD
xlm-roberta-base-finetuned-PersianQuAD is a question answering model from Z-Jafari. Use it when the input is a question plus a passage. 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
- Question Answering
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Dec 14, 2025
- Updated
- Dec 14, 2025
- SHA
- baa43fed
Try a prompt
Base models
Datasets
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. -->
xlm-roberta-base-finetuned-PersianQuAD-3epochs
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8643
- {'exact_match': 81.0, 'f1': 84.22979090740698}
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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
- fp16 = True
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1281 | 1.0 | 1463 | 0.9741 |
| 0.7462 | 2.0 | 2926 | 0.8346 |
| 0.5541 | 3.0 | 4389 | 0.8643 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Question Answering
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Languages
- fa
- Created
- Dec 14, 2025
- Updated
- Dec 14, 2025