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BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-ContaminationQAmodel_PubmedBERT
Shushant/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-ContaminationQAmodel_PubmedBERT
BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-ContaminationQAmodel_PubmedBERT is a question answering model from Shushant. 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
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 16, 2022
- SHA
- 71a293ac
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. -->
BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-ContaminationQAmodel_PubmedBERT
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.7515
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 22 | 3.9518 |
| No log | 2.0 | 44 | 3.2703 |
| No log | 3.0 | 66 | 2.9308 |
| No log | 4.0 | 88 | 2.7806 |
| No log | 5.0 | 110 | 2.6926 |
| No log | 6.0 | 132 | 2.7043 |
| No log | 7.0 | 154 | 2.7113 |
| No log | 8.0 | 176 | 2.7236 |
| No log | 9.0 | 198 | 2.7559 |
| No log | 10.0 | 220 | 2.7515 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Mar 2, 2022
- Updated
- Jan 16, 2022