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ClinicalBERT-Symptom2Disease
rchrdwllm/ClinicalBERT-Symptom2Disease
ClinicalBERT-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
- distilbert
- Access
- Public
- Created
- Sep 28, 2025
- Updated
- Sep 29, 2025
- SHA
- a5ddb188
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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. -->
ClinicalBERT-Symptom2Disease
This model is a fine-tuned version of medicalai/ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1251
- Accuracy: 0.9545
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: 4.823936931558756e-05
- train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 1.216 | 1.0 | 22 | 0.6698 | 0.8636 |
| 0.3317 | 2.0 | 44 | 0.1399 | 0.9773 |
| 0.0619 | 3.0 | 66 | 0.0985 | 0.9545 |
| 0.0248 | 4.0 | 88 | 0.1147 | 0.9773 |
| 0.0158 | 5.0 | 110 | 0.1251 | 0.9545 |
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
- distilbert
- Created
- Sep 28, 2025
- Updated
- Sep 29, 2025