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---
library_name: transformers
license: apache-2.0
datasets:
- Mozilla/smart_ner_dataset
language:
- en
base_model:
- distilbert/distilbert-base-uncased
pipeline_tag: token-classification
---
# 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](https://huggingface.co/distilbert/distilbert-base-uncased)
### Model Sources
- **Repository:** [Mozilla Smart Intent Project](https://github.com/mozilla/smart_intent)
### 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}
}
``` |