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vipubmed-deberta-base-finetuned-squad
namngo/vipubmed-deberta-base-finetuned-squad
vipubmed-deberta-base-finetuned-squad is a question answering model from namngo. 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
- deberta-v2
- Access
- Public
- Created
- Aug 14, 2023
- Updated
- Aug 16, 2023
- SHA
- 34b4bd41
Try a prompt
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. -->
vipubmed-deberta-base-finetuned-squad
This model is a fine-tuned version of manhtt-079/vipubmed-deberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.1007
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5629 | 1.0 | 6458 | 1.6738 |
| 1.1718 | 2.0 | 12916 | 1.6706 |
| 0.933 | 3.0 | 19374 | 1.8478 |
| 0.6312 | 4.0 | 25832 | 2.0736 |
| 0.4321 | 5.0 | 32290 | 2.6935 |
| 0.2869 | 6.0 | 38748 | 3.5266 |
| 0.1894 | 7.0 | 45206 | 4.1007 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Question Answering
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Aug 14, 2023
- Updated
- Aug 16, 2023