clinicalBERT-section-classification-v1 – AI Model by NazzX1 | AlphaNeural AI

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NazzX1/
clinicalBERT-section-classification-v1

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text-classification

generated_from_trainer

medicalai/ClinicalBERT

autotrain_compatible

endpoints_compatible

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section-classification

This model is a fine-tuned version of medicalai/ClinicalBERT on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.2353
Accuracy: 0.7392
Precision: 0.6439
Recall: 0.7392
F1: 0.6845

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: 4
eval_batch_size: 4
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	434	1.2791	0.6882	0.6056	0.6882	0.6399
1.3149	2.0	868	1.2669	0.7204	0.6216	0.7204	0.6674
1.2335	3.0	1302	1.2441	0.7419	0.6477	0.7419	0.6869
1.2607	4.0	1736	1.2353	0.7392	0.6439	0.7392	0.6845

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Tokenizers 0.21.1