bert-finetuned-ner

KellyShiiii/bert-finetuned-ner

bert-finetuned-ner is a token classification model from KellyShiiii. 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: xlm-roberta
Access: Public
Created: Oct 25, 2022
Updated: Oct 31, 2022
SHA: 459a4c27

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Model card

From the Hugging Face model README

bert-finetuned-ner

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

Loss: 0.6370
Precision: 0.5313
Recall: 0.4530
F1: 0.4891
Accuracy: 0.9290

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
No log	1.0	125	0.5387	0.2190	0.0552	0.0882	0.8991
No log	2.0	250	0.4241	0.3430	0.1750	0.2317	0.9117
No log	3.0	375	0.4721	0.3502	0.1786	0.2366	0.9088
0.1529	4.0	500	0.6204	0.4300	0.2320	0.3014	0.9134
0.1529	5.0	625	0.6479	0.4470	0.2486	0.3195	0.9104
0.1529	6.0	750	0.4640	0.4532	0.4015	0.4258	0.9220
0.1529	7.0	875	0.5170	0.4288	0.4217	0.4253	0.9224
0.0229	8.0	1000	0.5846	0.5524	0.4273	0.4818	0.9233
0.0229	9.0	1125	0.5569	0.4644	0.4328	0.4480	0.9234
0.0229	10.0	1250	0.5818	0.5502	0.4438	0.4913	0.9258
0.0229	11.0	1375	0.6183	0.5607	0.4254	0.4838	0.9231
0.0048	12.0	1500	0.6148	0.5385	0.4254	0.4753	0.9250
0.0048	13.0	1625	0.6271	0.4896	0.4328	0.4594	0.9255
0.0048	14.0	1750	0.6475	0.5668	0.4217	0.4836	0.9267
0.0048	15.0	1875	0.6428	0.5704	0.4328	0.4921	0.9282
0.0016	16.0	2000	0.6577	0.5487	0.4254	0.4793	0.9270
0.0016	17.0	2125	0.6688	0.5556	0.4144	0.4747	0.9262
0.0016	18.0	2250	0.6481	0.5434	0.4383	0.4852	0.9282
0.0016	19.0	2375	0.6432	0.5428	0.4438	0.4883	0.9289
0.0007	20.0	2500	0.6370	0.5313	0.4530	0.4891	0.9290

Framework versions

Transformers 4.23.1
Pytorch 1.8.0
Datasets 2.6.1
Tokenizers 0.13.1

Task: Token Classification
Library: transformers
Type: xlm-roberta
Created: Oct 25, 2022
Updated: Oct 31, 2022