bert-base-NER

doodlevelyn/bert-base-NER

bert-base-NER is a token classification model from doodlevelyn. 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: bert
Access: Public
Created: Oct 26, 2022
Updated: Oct 26, 2022
SHA: b1d4c150

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Model card

From the Hugging Face model README

bert-base-NER

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

Loss: 0.4459
Precision: 0.3972
Recall: 0.2378
F1: 0.2975
Accuracy: 0.9571

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0006	1.0	7365	0.3996	0.4030	0.2121	0.2780	0.9573
0.0001	2.0	14730	0.3969	0.3798	0.2371	0.2920	0.9570
0.0	3.0	22095	0.4459	0.3972	0.2378	0.2975	0.9571

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
Created: Oct 26, 2022
Updated: Oct 26, 2022