distilbert-ner-email-org

Zefty/distilbert-ner-email-org

distilbert-ner-email-org is a fine-tuned version of dslim/distilbert-NER on a set of job application emails. The model is fine-tuned specifically to identify the organizations (ORG) entity, thus it CANNOT identify location (LOC), person (PER), and Miscellaneous (MISC), which is available in the original model. This model is fine-tuned specifically to identify the organizations for a personal side-project of mine to extract out companies from job application emails.

How to use

This model can be utilized with the Transformers pipeline for NER.

from transformers import AutoTokenizer, AutoModelForTokenClassification
from transformers import pipeline

tokenizer = AutoTokenizer.from_pretrained("Zefty/distilbert-ner-email-org")
model = AutoModelForTokenClassification.from_pretrained("Zefty/distilbert-ner-email-org")

nlp = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="first")
example = "Thank you for Applying to Amazon!"

ner_results = nlp(example)
print(ner_results)

Training data

This model was fine-tuned on a set of job application emails. Instead of using the full tokens from the CoNLL-2003 English Dataset, this dataset only includes the ORG token.

Eval results