bert-finetuned-ner3

NineArtsDragon/bert-finetuned-ner3

bert-finetuned-ner3 is a token classification model from NineArtsDragon. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Nov 11, 2022
Updated: Nov 11, 2022
SHA: 365a9dbf

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Model card

From the Hugging Face model README

bert-finetuned-ner3

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0002
Precision: 0.9795
Recall: 0.9922
F1: 0.9858
Accuracy: 0.9999
Name Precision: 0.9892
Name Recall: 0.9946
Name F1: 0.9919
Dob Precision: 0.9707
Dob Recall: 0.9900
Dob F1: 0.9803

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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy	Name Precision	Name Recall	Name F1	Dob Precision	Dob Recall	Dob F1
No log	1.0	108	0.0024	0.7581	0.9766	0.8536	0.9989	0.9579	0.9891	0.9733	0.6340	0.9652	0.7653
No log	2.0	216	0.0016	0.8519	0.9558	0.9009	0.9995	0.9624	0.9728	0.9676	0.7683	0.9403	0.8456
No log	3.0	324	0.0007	0.9193	0.9766	0.9471	0.9998	0.9784	0.9837	0.9810	0.8705	0.9701	0.9176
No log	4.0	432	0.0006	0.9305	0.9740	0.9518	0.9998	0.9838	0.9891	0.9864	0.8853	0.9602	0.9212
0.0023	5.0	540	0.0007	0.8929	0.9532	0.9221	0.9997	0.9733	0.9891	0.9811	0.8259	0.9204	0.8706
0.0023	6.0	648	0.0003	0.9646	0.9922	0.9782	0.9999	0.9892	0.9946	0.9919	0.9431	0.9900	0.9660
0.0023	7.0	756	0.0006	0.9259	0.9740	0.9494	0.9998	0.9581	0.9946	0.976	0.8972	0.9552	0.9253
0.0023	8.0	864	0.0007	0.9322	0.9636	0.9476	0.9998	0.9945	0.9891	0.9918	0.8791	0.9403	0.9087
0.0023	9.0	972	0.0002	0.9821	0.9948	0.9884	0.9999	0.9946	0.9946	0.9946	0.9709	0.9950	0.9828
0.0008	10.0	1080	0.0003	0.9646	0.9922	0.9782	0.9999	0.9946	0.9946	0.9946	0.9387	0.9900	0.9637
0.0008	11.0	1188	0.0002	0.9846	0.9974	0.9910	0.9999	0.9946	0.9946	0.9946	0.9757	1.0	0.9877
0.0008	12.0	1296	0.0002	0.9720	0.9922	0.9820	0.9999	0.9786	0.9946	0.9865	0.9660	0.9900	0.9779
0.0008	13.0	1404	0.0002	0.9745	0.9922	0.9833	0.9999	0.9839	0.9946	0.9892	0.9660	0.9900	0.9779
0.0004	14.0	1512	0.0002	0.9846	0.9974	0.9910	0.9999	0.9839	0.9946	0.9892	0.9853	1.0	0.9926
0.0004	15.0	1620	0.0003	0.9744	0.9896	0.9820	0.9999	0.9786	0.9946	0.9865	0.9706	0.9851	0.9778
0.0004	16.0	1728	0.0002	0.9769	0.9896	0.9832	0.9999	0.9838	0.9891	0.9864	0.9707	0.9900	0.9803
0.0004	17.0	1836	0.0003	0.9693	0.9844	0.9768	0.9999	0.9892	0.9946	0.9919	0.9515	0.9751	0.9631
0.0004	18.0	1944	0.0002	0.9846	0.9948	0.9897	1.0000	0.9892	0.9946	0.9919	0.9804	0.9950	0.9877
0.0002	19.0	2052	0.0002	0.9795	0.9922	0.9858	0.9999	0.9892	0.9946	0.9919	0.9707	0.9900	0.9803
0.0002	20.0	2160	0.0002	0.9795	0.9922	0.9858	0.9999	0.9892	0.9946	0.9919	0.9707	0.9900	0.9803

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Nov 11, 2022
Updated: Nov 11, 2022