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bert-covidqa-5
hung200504/bert-covidqa-5
bert-covidqa-5 is a question answering model from hung200504. 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
- Oct 23, 2023
- Updated
- Oct 23, 2023
- SHA
- 58fb0314
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. -->
bert-covidqa-5
This model is a fine-tuned version of timpal0l/mdeberta-v3-base-squad2 on the covid_qa_deepset dataset. It achieves the following results on the evaluation set:
- Loss: 0.4190
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: 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5956 | 0.04 | 5 | 0.4016 |
| 0.3741 | 0.09 | 10 | 0.3879 |
| 0.3405 | 0.13 | 15 | 0.4240 |
| 0.4372 | 0.18 | 20 | 0.4102 |
| 0.2592 | 0.22 | 25 | 0.4534 |
| 0.3534 | 0.26 | 30 | 0.4571 |
| 0.4268 | 0.31 | 35 | 0.4107 |
| 0.2663 | 0.35 | 40 | 0.4166 |
| 0.143 | 0.39 | 45 | 0.4345 |
| 0.2494 | 0.44 | 50 | 0.5575 |
| 0.8953 | 0.48 | 55 | 0.6172 |
| 0.5504 | 0.53 | 60 | 0.4879 |
| 0.6411 | 0.57 | 65 | 0.3718 |
| 0.5454 | 0.61 | 70 | 0.3929 |
| 0.4441 | 0.66 | 75 | 0.3641 |
| 0.2922 | 0.7 | 80 | 0.3638 |
| 0.491 | 0.75 | 85 | 0.3785 |
| 0.4362 | 0.79 | 90 | 0.3938 |
| 0.1633 | 0.83 | 95 | 0.4162 |
| 0.6762 | 0.88 | 100 | 0.4321 |
| 0.3111 | 0.92 | 105 | 0.4241 |
| 0.3453 | 0.96 | 110 | 0.4190 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
- Task
- Question Answering
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Oct 23, 2023
- Updated
- Oct 23, 2023