|
--- |
|
language: bn |
|
datasets: |
|
- wikiann |
|
examples: |
|
widget: |
|
- text: "আমি, সাকিব হোসেন হিমেল, ডাটা সায়েন্সে স্নাতকোত্তর করছি, বর্তমানে জার্মানির বার্লিনে থাকি, গত বছর বাংলাদেশ থেকে এসেছি।" |
|
example_title: "Sentence_1" |
|
- text: "হোর্হেলুইস বোর্হেস" |
|
example_title: "Sentence_2" |
|
- text: "বাংলাদেশ জাতীয় ক্রিকেট দল" |
|
example_title: "Sentence_3" |
|
- text: "কুড়িগ্রাম উপজেলা" |
|
example_title: "Sentence_4" |
|
- text: "লিওনার্দো দা ভিঞ্চি" |
|
example_title: "Sentence_5" |
|
- text: "রিয়াল মাদ্রিদ ফুটবল ক্লাব" |
|
example_title: "Sentence_6" |
|
--- |
|
|
|
<h1>Named Entity Recognition on Bangla Language</h1> |
|
Fine Tuning BERT for NER on Bengali Language Tagging using HuggingFace |
|
|
|
|
|
## Correspondence 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 | |
|
|
|
<h1>Evaluation and Validation</h1> |
|
|
|
| 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 |
|
|
|
```py |
|
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 |
|
``` |
|
|