
<h1>Bengali Named Entity Recognition</h1>
Fine-tuning bert-base-multilingual-cased on Wikiann dataset for performing NER on Bengali language.


## Label ID and its corresponding 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>Results</h1>

| Name | Overall F1 | LOC F1 | ORG F1 | PER F1 |
| ---- | -------- | ----- | ---- | ---- |
| Train set | 0.997927 | 0.998246 | 0.996613 | 0.998769 |
| Validation set | 0.970187 | 0.969212 | 0.956831 | 0.982079 |
| Test set | 0.9673011 | 0.967120 |  0.963614 | 0.970938 |

Example
```py
from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline

tokenizer = AutoTokenizer.from_pretrained("Suchandra/bengali_language_NER")
model = AutoModelForTokenClassification.from_pretrained("Suchandra/bengali_language_NER")

nlp = pipeline("ner", model=model, tokenizer=tokenizer)
example = "মারভিন দি মারসিয়ান"

ner_results = nlp(example)
ner_results
```

{"language": "bn", "datasets": ["wikiann"], "widget": [{"text": "\u09ae\u09be\u09b0\u09ad\u09bf\u09a8 \u09a6\u09bf \u09ae\u09be\u09b0\u09b8\u09bf\u09af\u09bc\u09be\u09a8", "example_title": "Sentence_1"}, {"text": "\u09b2\u09bf\u0993\u09a8\u09be\u09b0\u09cd\u09a6\u09cb \u09a6\u09be \u09ad\u09bf\u099e\u09cd\u099a\u09bf", "example_title": "Sentence_2"}, {"text": "\u09ac\u09b8\u09a8\u09bf\u09af\u09bc\u09be \u0993 \u09b9\u09be\u09b0\u09cd\u099c\u09c7\u0997\u09cb\u09ad\u09bf\u09a8\u09be", "example_title": "Sentence_3"}, {"text": "\u09b8\u09be\u0989\u09a5 \u0987\u09b8\u09cd\u099f \u0987\u0989\u09a8\u09bf\u09ad\u09be\u09b0\u09cd\u09b8\u09bf\u099f\u09bf", "example_title": "Sentence_4"}, {"text": "\u09ae\u09be\u09a8\u09bf\u0995 \u09ac\u09a8\u09cd\u09a6\u09cd\u09af\u09cb\u09aa\u09be\u09a7\u09cd\u09af\u09be\u09af\u09bc \u09b2\u09c7\u0996\u0995", "example_title": "Sentence_5"}]}
transformers pytorch safetensors bert token-classification bn dataset:wikiann autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #token-classification #bn #dataset-wikiann #autotrain_compatible #endpoints_compatible #region-us 

Bengali Named Entity Recognition
================================


Fine-tuning bert-base-multilingual-cased on Wikiann dataset for performing NER on Bengali language.
Label ID and its corresponding label name
-----------------------------------------



Results
=======



Example



TAGS
#transformers #pytorch #safetensors #bert #token-classification #bn #dataset-wikiann #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #safetensors #bert #token-classification #bn #dataset-wikiann #autotrain_compatible #endpoints_compatible #region-us 
