bert-finetuned-ner-30

yubol/bert-finetuned-ner-30

bert-finetuned-ner-30 is a token classification model from yubol. 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: Oct 27, 2022
Updated: Oct 27, 2022
SHA: 6678a71f

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Model card

From the Hugging Face model README

bert-finetuned-ner

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: 0.0453
Precision: 0.9275
Recall: 0.9492
F1: 0.9382
Accuracy: 0.9934

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: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	407	0.0539	0.8283	0.8758	0.8514	0.9866
0.1524	2.0	814	0.0333	0.8931	0.9123	0.9026	0.9915
0.0381	3.0	1221	0.0345	0.8835	0.9280	0.9052	0.9906
0.0179	4.0	1628	0.0351	0.8890	0.9361	0.9119	0.9909
0.0089	5.0	2035	0.0310	0.9102	0.9372	0.9235	0.9924
0.0089	6.0	2442	0.0344	0.9198	0.9383	0.9289	0.9922
0.0057	7.0	2849	0.0331	0.9144	0.9448	0.9294	0.9931
0.0039	8.0	3256	0.0340	0.9144	0.9481	0.9309	0.9928
0.0027	9.0	3663	0.0423	0.9032	0.9481	0.9251	0.9921
0.0018	10.0	4070	0.0373	0.9047	0.9507	0.9271	0.9923
0.0018	11.0	4477	0.0448	0.8932	0.9474	0.9195	0.9910
0.0014	12.0	4884	0.0380	0.9079	0.9474	0.9272	0.9928
0.0015	13.0	5291	0.0360	0.9231	0.9474	0.9351	0.9936
0.0013	14.0	5698	0.0378	0.9243	0.9456	0.9348	0.9935
0.0013	15.0	6105	0.0414	0.9197	0.9496	0.9344	0.9930
0.0009	16.0	6512	0.0405	0.9202	0.9478	0.9338	0.9929
0.0009	17.0	6919	0.0385	0.9305	0.9441	0.9373	0.9933
0.0006	18.0	7326	0.0407	0.9285	0.9437	0.9360	0.9934
0.0009	19.0	7733	0.0428	0.9203	0.9488	0.9343	0.9929
0.0006	20.0	8140	0.0455	0.9232	0.9536	0.9382	0.9928
0.0004	21.0	8547	0.0462	0.9261	0.9529	0.9393	0.9930
0.0004	22.0	8954	0.0423	0.9359	0.9492	0.9425	0.9940
0.0005	23.0	9361	0.0446	0.9180	0.9529	0.9351	0.9931
0.0005	24.0	9768	0.0430	0.9361	0.9467	0.9413	0.9938
0.0002	25.0	10175	0.0436	0.9322	0.9496	0.9408	0.9935
0.0002	26.0	10582	0.0440	0.9275	0.9492	0.9382	0.9935
0.0002	27.0	10989	0.0450	0.9272	0.9488	0.9379	0.9932
0.0002	28.0	11396	0.0445	0.9304	0.9470	0.9386	0.9935
0.0003	29.0	11803	0.0449	0.9278	0.9481	0.9378	0.9934
0.0001	30.0	12210	0.0453	0.9275	0.9492	0.9382	0.9934

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Oct 27, 2022
Updated: Oct 27, 2022