Fine-tuned LoRA Token classification on distilbert
This is a fine-tuned LoRA token classifier on distilbert, designed for NER on multiple categories PERSON, ORG, CITY, STATE, CITY_STATE.
Model Details
Model Description
This model is based on distilbert/distilbert-base-uncased and fine-tuned using LoRA for token classification. The fine-tuning process adapts the model to predict tokens across 10 categories:
"O" # Outside any named entity
"B-PER" # Beginning of a person entity
"I-PER" # Inside a person entity
"B-ORG" # Beginning of an organization entity
"I-ORG" # Inside an organization entity
"B-CITY" # Beginning of a city entity
"I-CITY" # Inside a city entity
"B-STATE" # Beginning of a state entity
"I-STATE" # Inside a state entity
"B-CITYSTATE" # Beginning of a city_state entity
"I-CITYSTATE" # Inside a city_state entity
- Developed by: Mozilla
- Language(s): English (
en
) - License: Apache-2.0
- Fine-tuned from: distilbert/distilbert-base-uncased
Model Sources
- Repository: Mozilla Smart Intent Project
Citation
If you use this model, please cite it as:
@misc{mozilla_distilbert_lora_ner,
title = {Fine-tuned LoRA Token Classifier on DistilBERT},
author = {Mozilla},
year = {2024},
url = {https://huggingface.co./Mozilla/distilbert-finetuned-LoRA-token-classifier},
license = {Apache-2.0}
}
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Base model
distilbert/distilbert-base-uncased