---
base_model: bert-base-uncased
datasets:
- AAU-NLP/hifi-kpi-lite
language:
- en
library_name: transformers
model_name: Lite-BERT-SL
pipeline_tag: token-classification
tags:
- financial-nlp
- named-entity-recognition
- sequence-labeling
- finance
license: cc-by-4.0
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: 'Lite-BERT-SL: Sequence Labeling for HiFi-KPI Lite'
size_categories: 10K<n<100K
---

# Lite-BERT-SL: Sequence Labeling for HiFi-KPI Lite

Lite-BERT-SL is a **BERT-based sequence labeling model** fine-tuned on the **HiFi-KPI Lite** dataset. This model was introduced in the paper [HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings](https://huggingface.co/papers/2502.15411).

## Model Description
The model is designed for the hierarchical extraction of Key Performance Indicators (KPIs) from financial earnings filings (SEC 10-K and 10-Q reports). While the full HiFi-KPI dataset contains a massive taxonomy of iXBRL tags, Lite-BERT-SL is fine-tuned on a manually curated subset focusing on four expert-mapped KPI clusters:
- **Revenues**
- **Earnings**
- **EPS** (Earnings Per Share)
- **EBIT** (Earnings Before Interest and Taxes)

- **Developed by:** Rasmus Aavang, Giovanni Rizzi, Rasmus Bøggild, Alexandre Iolov, Mike Zhang, Johannes Bjerva
- **Model type:** Token Classification (Sequence Labeling)
- **Base Model:** `bert-base-uncased`
- **Language:** English

## Use Cases
- Identifying and extracting generalized financial KPIs from earnings filings.
- Automating the parsing of SEC 10-K and 10-Q reports for structured data extraction.
- Assisting in the alignment of financial text with iXBRL taxonomies.

## Performance
According to the paper, encoder-based models achieve over 0.906 macro-F1 on the HiFi-KPI Lite classification task. For detailed performance metrics, please refer to the [paper](https://huggingface.co/papers/2502.15411) and the [HiFi-KPI Lite dataset page](https://huggingface.co/datasets/AAU-NLP/hifi-kpi-lite).

## Dataset & Code
- **Paper**: [HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings](https://huggingface.co/papers/2502.15411)
- **Dataset**: [HiFi-KPI Lite on Hugging Face](https://huggingface.co/datasets/AAU-NLP/hifi-kpi-lite)
- **Code**: [Official HiFi-KPI GitHub Repository](https://github.com/aaunlp/HiFi-KPI)

## Citation
If you use this model or the dataset in your research, please cite:

```bibtex
@article{aavang2025hifikpi,
  title={HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings},
  author={Aavang, Rasmus and Rizzi, Giovanni and B{\o}ggild, Rasmus and Iolov, Alexandre and Zhang, Mike and Bjerva, Johannes},
  journal={arXiv preprint arXiv:2502.15411},
  year={2025}
}
```