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deberta-base-finetuned-aqa
stevemobs/deberta-base-finetuned-aqa
deberta-base-finetuned-aqa 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 24, 2022
- Updated
- May 24, 2022
- SHA
- 304db0cf
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. -->
deberta-base-finetuned-aqa
This model is a fine-tuned version of microsoft/deberta-base on the adversarial_qa dataset. It achieves the following results on the evaluation set:
- Loss: 1.6394
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 |
|---|---|---|---|
| 2.1054 | 1.0 | 2527 | 1.6947 |
| 1.5387 | 2.0 | 5054 | 1.6394 |
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 24, 2022
- Updated
- May 24, 2022