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Introduction of bert-large-uncased-ner-conll2003

Model Details of bert-large-uncased-ner-conll2003

bert-large-uncased-ner

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

Loss: 0.0591
Precision: 0.9465
Recall: 0.9568
F1: 0.9517
Accuracy: 0.9877

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: 5e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1702	1.0	878	0.0578	0.9202	0.9347	0.9274	0.9836
0.0392	2.0	1756	0.0601	0.9306	0.9448	0.9377	0.9851
0.0157	3.0	2634	0.0517	0.9405	0.9544	0.9474	0.9875
0.0057	4.0	3512	0.0591	0.9465	0.9568	0.9517	0.9877

Framework versions

Transformers 4.8.2
Pytorch 1.8.1+cu111
Datasets 1.8.0
Tokenizers 0.10.3

Runs of andi611 bert-large-uncased-ner-conll2003 on huggingface.co

Total runs

24-hour runs

-1

3-day runs

-3

7-day runs

-2

30-day runs

More Information About bert-large-uncased-ner-conll2003 huggingface.co Model

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bert-large-uncased-ner-conll2003 huggingface.co Url

https://huggingface.co/andi611/bert-large-uncased-ner-conll2003

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bert-large-uncased-ner-conll2003 install

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