This model is a fine-tuned version of emilyalsentzer/Bio_ClinicalBERT on the ncbi_disease dataset. It achieves the following results on the evaluation set:

Loss: 0.0623
Precision: 0.7953
Recall: 0.8590
F1: 0.8259
Accuracy: 0.9841

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: 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1204	1.0	680	0.0536	0.7417	0.8247	0.7810	0.9824
0.0386	2.0	1360	0.0542	0.7808	0.8463	0.8122	0.9831
0.0144	3.0	2040	0.0623	0.7953	0.8590	0.8259	0.9841

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1

adigo/bert-finetuned-ner

bert-finetuned-ner

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

adigo/
bert-finetuned-ner