Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0775	1.0	1756	0.0694	0.8912	0.9273	0.9089	0.9817
0.0377	2.0	3512	0.0707	0.9245	0.9445	0.9344	0.9850
0.0243	3.0	5268	0.0671	0.9281	0.9465	0.9372	0.9855
0.0145	4.0	7024	0.0734	0.9353	0.9507	0.9429	0.9859
0.006	5.0	8780	0.0741	0.9341	0.9520	0.9430	0.9867

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

How to use and it's democase

from transformers import pipeline

model_checkpoint = "amannagrawall002/bert-finetuned-ner" token_classifier = pipeline( "token-classification", model=model_checkpoint, aggregation_strategy="simple" )

print(token_classifier("My name is Sylvain and I work at Hugging Face in Brooklyn."))

[{'entity_group': 'PER', 'score': 0.9997023, 'word': 'Sylvain', 'start': 11, 'end': 18}, {'entity_group': 'ORG', 'score': 0.995275, 'word': 'Hugging Face', 'start': 33, 'end': 45}, {'entity_group': 'LOC', 'score': 0.9987465, 'word': 'Brooklyn', 'start': 49, 'end': 57}]