BERT-ner

Sadashiv/BERT-ner

BERT-ner is a token classification model from Sadashiv. 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: Jul 21, 2023
Updated: Jul 21, 2023
SHA: 3b2db08d

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Base models

Datasets

conll2003

Spaces

Sadashiv/BERT-NER

Model card

From the Hugging Face model README

BERT-ner

This model is a fine-tuned version of bert-base-uncased on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0664
Precision: 0.9449
Recall: 0.9516
F1: 0.9482
Accuracy: 0.9872

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0252	1.0	878	0.0652	0.9414	0.9419	0.9417	0.9854
0.0121	2.0	1756	0.0615	0.9407	0.9498	0.9452	0.9867
0.0079	3.0	2634	0.0664	0.9449	0.9516	0.9482	0.9872

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Jul 21, 2023
Updated: Jul 21, 2023