---
base_model: bert-base-uncased
datasets:
- AAU-NLP/HiFi-KPI
language:
- en
library_name: transformers
model_name: Cal-BERT-SL1000
pipeline_tag: token-classification
tags:
- financial NLP
- named entity recognition
- sequence labeling
- structured extraction
- hierarchical taxonomy
- XBRL
- iXBRL
- SEC filings
- financial-information-extraction
task_categories:
- token-classification
task_ids:
- named-entity-recognition
- financial-information-extraction
pretty_name: 'Cal-BERT-SL1000: Sequence Labeling for Calculation Taxonomy KPI Extraction'
---

## **Cal-BERT-SL1000**

### **Model Description**  
Cal-BERT-SL1000 is a **BERT-based sequence labeling model** fine-tuned on the **[HiFi-KPI dataset](https://huggingface.co/datasets/AAU-NLP/HiFi-KPI)** for extracting **financial key performance indicators (KPIs)** from **SEC earnings filings (10-K & 10-Q)**. It specializes in identifying entities that are one level up the calculation taxonomy ($n=1$), such as `revenueAbstract`, `earnings`, and `financial ratios`, using **token classification**.

This model was introduced in the paper [HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings](https://huggingface.co/papers/2502.15411) by Rasmus Aavang, Giovanni Rizzi, Rasmus Bøggild, Alexandre Iolov, Mike Zhang (@jjzha), and Johannes Bjerva.

### **Use Cases**
- Extracting **financial KPIs** using **iXBRL calculation taxonomy**  
- **Financial document parsing** with entity recognition  

### **Performance**
- Trained on **1,000 most frequent labels** from the **[HiFi-KPI dataset](https://huggingface.co/datasets/AAU-NLP/HiFi-KPI)** with $n=1$ in the calculation taxonomy.

### **Dataset & Code**
- **Dataset**: [HiFi-KPI on Hugging Face](https://huggingface.co/datasets/AAU-NLP/HiFi-KPI)  
- **Official Code**: [HiFi-KPI GitHub Repository](https://github.com/aaunlp/HiFi-KPI)  

### **Citation**
```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}
}
```