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deberta-base-finetuned-aqa-newsqa
stevemobs/deberta-base-finetuned-aqa-newsqa
deberta-base-finetuned-aqa-newsqa is a question answering model from stevemobs. 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
- Access
- Public
- Created
- May 29, 2022
- Updated
- May 29, 2022
- SHA
- e3967610
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. -->
deberta-base-finetuned-aqa-newsqa
This model is a fine-tuned version of stevemobs/deberta-base-finetuned-aqa on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7657
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6883 | 1.0 | 17307 | 0.7325 |
| 0.4807 | 2.0 | 34614 | 0.7657 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Task
- Question Answering
- Library
- transformers
- Type
- deberta
- License
- mit
- Created
- May 29, 2022
- Updated
- May 29, 2022