metadata

library_name: transformers
license: cc0-1.0
base_model: bionlp/bluebert_pubmed_uncased_L-24_H-1024_A-16
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: medical-ner-bluebert
    results: []

medical-ner-bluebert

This model is a fine-tuned version of bionlp/bluebert_pubmed_uncased_L-24_H-1024_A-16 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0894
Precision: 0.9365
Recall: 0.9705
F1: 0.9532
Accuracy: 0.9810

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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	90	0.7138	0.5501	0.6082	0.5777	0.7757
No log	2.0	180	0.6697	0.5391	0.7574	0.6298	0.7863
No log	3.0	270	0.4996	0.6284	0.8024	0.7048	0.8429
No log	4.0	360	0.3957	0.6779	0.8332	0.7476	0.8760
No log	5.0	450	0.2886	0.7603	0.8658	0.8096	0.9160
0.4932	6.0	540	0.2345	0.8026	0.8839	0.8413	0.9321
0.4932	7.0	630	0.2061	0.8290	0.9121	0.8686	0.9419
0.4932	8.0	720	0.1715	0.8537	0.9226	0.8868	0.9518
0.4932	9.0	810	0.1454	0.8701	0.9374	0.9025	0.9603
0.4932	10.0	900	0.1422	0.8857	0.9437	0.9137	0.9635
0.4932	11.0	990	0.1134	0.9081	0.9516	0.9293	0.9718
0.0935	12.0	1080	0.1147	0.9075	0.9582	0.9322	0.9722
0.0935	13.0	1170	0.1039	0.9165	0.9616	0.9385	0.9757
0.0935	14.0	1260	0.0978	0.9256	0.9658	0.9453	0.9774
0.0935	15.0	1350	0.0925	0.9283	0.9671	0.9473	0.9797
0.0935	16.0	1440	0.0873	0.9378	0.9679	0.9526	0.9813
0.0301	17.0	1530	0.0927	0.9334	0.9703	0.9515	0.9803
0.0301	18.0	1620	0.0903	0.9355	0.97	0.9525	0.9804
0.0301	19.0	1710	0.0890	0.9373	0.9711	0.9539	0.9811
0.0301	20.0	1800	0.0894	0.9365	0.9705	0.9532	0.9810

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3