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biobert-v1.1-finetuned-pubmedqa
blizrys/biobert-v1.1-finetuned-pubmedqa
biobert-v1.1-finetuned-pubmedqa is a text classification model from blizrys. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Sep 13, 2021
- SHA
- d36bc441
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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. -->
biobert-v1.1-finetuned-pubmedqa
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7737
- Accuracy: 0.7
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 57 | 0.8810 | 0.56 |
| No log | 2.0 | 114 | 0.8139 | 0.62 |
| No log | 3.0 | 171 | 0.7963 | 0.68 |
| No log | 4.0 | 228 | 0.7709 | 0.66 |
| No log | 5.0 | 285 | 0.7931 | 0.64 |
| No log | 6.0 | 342 | 0.7420 | 0.7 |
| No log | 7.0 | 399 | 0.7654 | 0.7 |
| No log | 8.0 | 456 | 0.7756 | 0.68 |
| 0.5849 | 9.0 | 513 | 0.7605 | 0.68 |
| 0.5849 | 10.0 | 570 | 0.7737 | 0.7 |
Framework versions
- Transformers 4.10.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Hf Inference
- live
- Created
- Mar 2, 2022
- Updated
- Sep 13, 2021