Medical-NER-finetuned-ner

jaggernaut007/Medical-NER-finetuned-ner

Medical-NER-finetuned-ner is a token classification model from jaggernaut007. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Token Classification
Library: transformers
License: mit
Model type: deberta-v2
Access: Public
Created: Apr 13, 2024
Updated: Apr 22, 2024
SHA: cf878dd4

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Base models

Model card

From the Hugging Face model README

Medical-NER-finetuned-ner

This model is a fine-tuned version of Clinical-AI-Apollo/Medical-NER on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2045
Precision: 0.9394
Recall: 0.9282
F1: 0.9338
Accuracy: 0.9296

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-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.37	100	0.4486	0.8318	0.8662	0.8486	0.8331
No log	0.75	200	0.3747	0.8608	0.8834	0.8720	0.8646
No log	1.12	300	0.3245	0.8801	0.8932	0.8866	0.8828
No log	1.49	400	0.2846	0.9128	0.9038	0.9083	0.9028
0.4808	1.87	500	0.2554	0.9199	0.9067	0.9133	0.9083
0.4808	2.24	600	0.2480	0.9270	0.9073	0.9171	0.9102
0.4808	2.61	700	0.2269	0.9271	0.9172	0.9221	0.9171
0.4808	2.99	800	0.2319	0.9270	0.9089	0.9179	0.9129
0.4808	3.36	900	0.2303	0.9284	0.9088	0.9185	0.9133
0.2633	3.73	1000	0.2246	0.9311	0.9111	0.9210	0.9155
0.2633	4.1	1100	0.2120	0.9343	0.9218	0.9280	0.9236
0.2633	4.48	1200	0.2111	0.9361	0.9222	0.9291	0.9243
0.2633	4.85	1300	0.2152	0.9320	0.9185	0.9252	0.9208
0.2633	5.22	1400	0.2068	0.9333	0.9227	0.9280	0.9239
0.2218	5.6	1500	0.2070	0.9360	0.9256	0.9308	0.9267
0.2218	5.97	1600	0.2045	0.9394	0.9282	0.9338	0.9296
0.2218	6.34	1700	0.2020	0.9357	0.9275	0.9316	0.9284
0.2218	6.72	1800	0.2054	0.9354	0.9227	0.9290	0.9246
0.2218	7.09	1900	0.2053	0.9372	0.9253	0.9312	0.9269

Framework versions

Transformers 4.39.3
Pytorch 2.2.2+cu121
Datasets 2.19.0
Tokenizers 0.15.2

Task: Token Classification
Library: transformers
Type: deberta-v2
License: mit
Created: Apr 13, 2024
Updated: Apr 22, 2024