Named Entity Recognition on Bangla Language
Fine Tuning BERT for NER on Bengali Language Tagging using HuggingFaceCorrespondence Label ID and Label Name
Label ID | Label Name |
---|---|
0 | O |
1 | B-PER |
2 | I-PER |
3 | B-ORG |
4 | I-ORG |
5 | B-LOC |
6 | I-LOC |
Evaluation and Validation
Name | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|
Train/Val set | 0.963899 | 0.964770 | 0.964334 | 0.981252 |
Test set | 0.952855 | 0.965105 | 0.958941 | 0.981349 |
Transformers AutoModelForTokenClassification
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("engineersakibcse47/NER_on_Bangla_Language")
model_ner = AutoModelForTokenClassification.from_pretrained("engineersakibcse47/NER_on_Bangla_Language")
pipe = pipeline("ner", model=model_ner, tokenizer=tokenizer, aggregation_strategy="simple")
sample = "বসনিয়া ও হার্জেগোভিনা"
result = pipe(sample)
result
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