BERT-Tamil

Ambareeshkumar/BERT-Tamil

BERT-Tamil is a token classification model from Ambareeshkumar. Use it when you need labels on individual words, such as names. It is set up for transformers.

<h1Tamil Named Entity Recognition</h1 Fine-tuning bert-base-multilingual-cased on Wikiann dataset for performing NER on Tamil language.

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At a glance

Task: Token Classification
Library: transformers
Model type: bert
Access: Public
Created: Dec 5, 2022
Updated: Dec 6, 2022
SHA: 8242b9a9

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Datasets

wikiann

Model card

From the Hugging Face model README

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

Step	Training Loss	Validation Loss	Overall Precision	Overall Recall	Overall F1	Overall Accuracy	Loc F1	Org F1	Per F1
1000	0.386900	0.300006	0.833469	0.824748	0.829086	0.912857	0.835343	0.781625	0.867752
2000	0.210200	0.251389	0.845455	0.842052	0.843750	0.924861	0.851711	0.790198	0.886515
3000	0.140000	0.264964	0.866952	0.856137	0.861510	0.930141	0.874872	0.818150	0.885203
4000	0.095400	0.298542	0.860871	0.882696	0.871647	0.935692	0.881348	0.829285	0.899245
5000	0.062200	0.296011	0.871805	0.878471	0.875125	0.938806	0.875434	0.850889	0.898148
6000	0.042200	0.320418	0.868416	0.879074	0.873713	0.937497	0.877588	0.833611	0.907737

Example

from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline
tokenizer = AutoTokenizer.from_pretrained("Ambareeshkumar/BERT-Tamil")
model = AutoModelForTokenClassification.from_pretrained("Ambareeshkumar/BERT-Tamil")
nlp = pipeline("ner", model=model, tokenizer=tokenizer)
example = "இந்திய"
ner_results = nlp(example)
ner_results

Task: Token Classification
Library: transformers
Type: bert
Languages: ta
Created: Dec 5, 2022
Updated: Dec 6, 2022