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Finetuning_Bert_ClinicalNotes_Diagnosis_Classification
ahmed792002/Finetuning_Bert_ClinicalNotes_Diagnosis_Classification
Finetuning_Bert_ClinicalNotes_Diagnosis_Classification is a text classification model from ahmed792002. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Dec 11, 2024
- Updated
- Oct 14, 2025
- SHA
- 0669e487
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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. -->
Finetuning_Bert_ClinicalNotes_Diagnosis_Classification
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0081
- Accuracy: 1.0
- F1: 1.0
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 219 | 0.1206 | 1.0 | 1.0 |
| No log | 2.0 | 438 | 0.0203 | 1.0 | 1.0 |
| 0.5546 | 3.0 | 657 | 0.0116 | 1.0 | 1.0 |
| 0.5546 | 4.0 | 876 | 0.0089 | 1.0 | 1.0 |
| 0.0153 | 5.0 | 1095 | 0.0081 | 1.0 | 1.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 11, 2024
- Updated
- Oct 14, 2025