bert-finetuned-ner – AI Model by sohamtiwari3120 | AlphaNeural AI

You can deploy this model and start earning money today!

sohamtiwari3120/
bert-finetuned-ner

like

0

token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

bert-finetuned-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: 0.0589
Overall Precision: 0.9362
Overall Recall: 0.9500
Overall F1: 0.9430
Overall Accuracy: 0.9873
Loc F1: 0.9616
Misc F1: 0.8783
Org F1: 0.9121
Per F1: 0.9797

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	Overall Precision	Overall Recall	Overall F1	Overall Accuracy	Loc F1	Misc F1	Org F1	Per F1
0.0745	1.0	1756	0.0556	0.9183	0.9345	0.9263	0.9848	0.9501	0.8499	0.8775	0.9765
0.0321	2.0	3512	0.0542	0.9346	0.9475	0.9410	0.9872	0.9618	0.8761	0.9073	0.9773
0.0172	3.0	5268	0.0589	0.9362	0.9500	0.9430	0.9873	0.9616	0.8783	0.9121	0.9797

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu102
Datasets 2.6.1
Tokenizers 0.13.1