bert-finetuned-ner – AI Model by Hudayday | AlphaNeural AI

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Hudayday/
bert-finetuned-ner

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-finetuned-ner

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

Loss: 0.0810
Precision: 0.9396
Recall: 0.9551
F1: 0.9473
Accuracy: 0.9878

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0221	1.0	1756	0.1039	0.9007	0.9278	0.9140	0.9797
0.0132	2.0	3512	0.0808	0.9286	0.9472	0.9378	0.9854
0.0092	3.0	5268	0.0827	0.9301	0.9488	0.9394	0.9857
0.006	4.0	7024	0.0781	0.9392	0.9542	0.9467	0.9878
0.0022	5.0	8780	0.0810	0.9396	0.9551	0.9473	0.9878

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2