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Persian-QA-Bert-V1
SeyedAli/Persian-QA-Bert-V1
Persian-QA-Bert-V1 is a question answering model from SeyedAli. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Sep 11, 2023
- Updated
- Nov 18, 2023
- SHA
- 6eea2deb
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. -->
result
This model is a fine-tuned version of HooshvareLab/bert-fa-base-uncased on SeyedAli/Persian-Text-QA dataset. It achieves the following results on the evaluation set:
- Loss: 5.0331
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.3247 | 1.0 | 1126 | 1.7615 |
| 1.4445 | 2.0 | 2252 | 1.8002 |
| 0.7653 | 3.0 | 3378 | 2.0806 |
| 0.4247 | 4.0 | 4504 | 2.6624 |
| 0.2502 | 5.0 | 5630 | 3.2961 |
| 0.168 | 6.0 | 6756 | 3.7767 |
| 0.0809 | 7.0 | 7882 | 4.3288 |
| 0.0544 | 8.0 | 9008 | 4.8516 |
| 0.0398 | 9.0 | 10134 | 4.9091 |
| 0.0102 | 10.0 | 11260 | 5.0331 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Languages
- fa
- Created
- Sep 11, 2023
- Updated
- Nov 18, 2023