ner_model_ep2

Polo123/ner_model_ep2

ner_model_ep2 is a token classification model from Polo123. Use it when you need labels on individual words, such as names. It is set up for transformers.

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

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At a glance

Task: Token Classification
Library: transformers
Model type: distilbert
Access: Public
Created: Jul 21, 2024
Updated: Jul 21, 2024
SHA: b517472b

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Model card

From the Hugging Face model README

ner_model_ep2

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3762
allergy Name F1: 0.7874
allergy Name Pres: 0.7751
allergy Name Rec: 0.8
cancer F1: 0.7143
cancer Pres: 0.7106
cancer Rec: 0.7180
chronic Disease F1: 0.7611
chronic Disease Pres: 0.7583
chronic Disease Rec: 0.7638
treatment F1: 0.7718
treatmen Prest: 0.7533
treatment Rec: 0.7913
Over All Precision: 0.7495
Over All Recall: 0.7704
Over All F1: 0.7598
Over All Accuracy: 0.8780

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	allergy Name F1	allergy Name Pres	allergy Name Rec	cancer F1	cancer Pres	cancer Rec	chronic Disease F1	chronic Disease Pres	chronic Disease Rec	treatment F1	treatmen Prest	treatment Rec	Over All Precision	Over All Recall	Over All F1	Over All Accuracy
0.4256	1.0	329	0.3561	0.7266	0.6896	0.7679	0.6592	0.6972	0.6251	0.7232	0.7719	0.6804	0.7377	0.7443	0.7312	0.7457	0.6974	0.7207	0.8689
0.3248	2.0	658	0.3547	0.7836	0.7895	0.7778	0.6873	0.6813	0.6933	0.7480	0.7509	0.7451	0.7517	0.7121	0.7959	0.7232	0.7613	0.7417	0.8723
0.26	3.0	987	0.3655	0.7599	0.7196	0.8049	0.6904	0.6764	0.7050	0.7548	0.7620	0.7477	0.7672	0.7432	0.7928	0.7393	0.7633	0.7511	0.8753
0.225	4.0	1316	0.3662	0.7878	0.7783	0.7975	0.7036	0.7308	0.6782	0.7603	0.7653	0.7554	0.7682	0.7504	0.7869	0.7539	0.7593	0.7566	0.8777
0.1968	5.0	1645	0.3762	0.7874	0.7751	0.8	0.7143	0.7106	0.7180	0.7611	0.7583	0.7638	0.7718	0.7533	0.7913	0.7495	0.7704	0.7598	0.8780

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

Task: Token Classification
Library: transformers
Type: distilbert
Created: Jul 21, 2024
Updated: Jul 21, 2024