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BioBERT-Symptom2Disease
rchrdwllm/BioBERT-Symptom2Disease
BioBERT-Symptom2Disease is a text classification model from rchrdwllm. 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
- Sep 28, 2025
- Updated
- Sep 29, 2025
- SHA
- 874c2afc
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Base models
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-Symptom2Disease
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9704
- Accuracy: 0.6364
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: 4.4346431315956026e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3808 | 1.0 | 3 | 1.3027 | 0.4091 |
| 1.2227 | 2.0 | 6 | 1.1699 | 0.6364 |
| 1.0889 | 3.0 | 9 | 1.0762 | 0.6591 |
| 1.0029 | 4.0 | 12 | 1.0024 | 0.6591 |
| 0.9398 | 5.0 | 15 | 0.9704 | 0.6364 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Sep 28, 2025
- Updated
- Sep 29, 2025