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bert-base-parsbert-uncased-finetuned-perQA
aminnaghavi/bert-base-parsbert-uncased-finetuned-perQA
bert-base-parsbert-uncased-finetuned-perQA is a question answering model from aminnaghavi. Use it when the input is a question plus a passage. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Question Answering
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jun 20, 2022
- Updated
- Jun 20, 2022
- SHA
- 9f0f7d00
Try a prompt
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. -->
bert-base-parsbert-uncased-finetuned-perQA
This model is a fine-tuned version of HooshvareLab/bert-base-parsbert-uncased on the persian_qa dataset. It achieves the following results on the evaluation set:
- Loss: 1.8648
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.9599 | 1.0 | 565 | 2.0185 |
| 1.8889 | 2.0 | 1130 | 1.8088 |
| 1.4282 | 3.0 | 1695 | 1.8648 |
Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- Created
- Jun 20, 2022
- Updated
- Jun 20, 2022