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Lite-BERT-SL

Token Classification
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Safetensors
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bert
financial NLP
named entity recognition
sequence labeling
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metadata
tags:
  - financial NLP
  - named entity recognition
  - sequence labeling
datasets:
  - AAU-NLP/hifi-kpi-lite
model_name: Lite-BERT-SL
library_name: transformers
pipeline_tag: token-classification
base_model: bert-base-uncased
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
language:
  - en
dataset_name: HiFi-KPI Lite
model_description: >
  Lite-BERT-SL is a **BERT-based sequence labeling model** fine-tuned on
  **HiFi-KPI Lite**, a manually curated subset of the 

  **HiFi-KPI dataset**. This dataset contains a smaller, expert-chosen set of
  **financial key performance indicators (KPIs)**.


  Unlike the full HiFi-KPI dataset, HiFi-KPI Lite focuses on **four
  expert-mapped KPI clusters** (e.g., revenue, earnings, 

  EPS, EBIT).
dataset_link: https://huggingface.co/datasets/AAU-NLP/hifi-kpi-lite
repo_link: https://github.com/rasmus393/HiFi-KPI

Lite-BERT-SL

Model Description

Lite-BERT-SL is a BERT-based sequence labeling model fine-tuned on the HiFi-KPI Lite dataset, which is a manually curated version of HiFi-KPI with four general KPI categories.

Use Cases

  • Identifying generalized KPIs from SEC 10-K and 10-Q reports
  • Financial document parsing with entity recognition

Performance

  • Trained on HiFi-KPI Lite, which includes a manually curated subset of financial KPIs For performance table see HiFi-KPI Lite

Dataset & Code