---
library_name: transformers, peft
tags: []
---

# Model Card for Model ID

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## Model Details

### Model Description

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This is the an implementation of the Token Classification as mentioned [here](https://huggingface.co/docs/peft/task_guides/token-classification-lora). A PEFT model has been fine tuned to a token classification task for Bio Entity recognition from base model of roberta-large. Objective is to identify BIO Named Entity Recognition.

Given a statement [ "During", "treatment", "with", "Hm", ",", "K562", "cells", "constitutively", "expressed", "c-myb", "mRNA", ",", "and", "50", "%", "of", "them", "began", "to", "synthesize", "hemoglobin", "(", "Hb", ")", "." ]

it would generate the tags [ 0, 0, 0, 3, 0, 7, 8, 0, 0, 9, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0 ]

And the label id categories are
{
    "O": 0,
    "B-DNA": 1,
    "I-DNA": 2,
    "B-protein": 3,
    "I-protein": 4,
    "B-cell_type": 5,
    "I-cell_type": 6,
    "B-cell_line": 7,
    "I-cell_line": 8,
    "B-RNA": 9,
    "I-RNA": 10
}

More details can be found [here](https://huggingface.co/datasets/tner/bionlp2004?row=18)

- **Developed by:** PEFT Example
- **Model type:** Token Classification using LLM
- **Finetuned from:** model roberta-large

### Model Sources [optional]

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- **Repository:** [More Information Needed]
- **Paper [optional]:** [More Information Needed]
- **Demo [optional]:** [More Information Needed]