---
license: apache-2.0
language:
- en
tags:
  - finance
  - exception-handling
  - reconciliation
  - classification
---

# BERT-Breaks (v0) – Coming Soon 🚧

**Status:** *Model training and evaluation planned – baseline placeholder repository.*

## Overview

`BERT-Breaks-v0` serves as the **vanilla BERT baseline** for the Exception Handling & Reconciliation project.  
It will be trained on the same corpus as our [`DistilBERT-Reconciler`](https://huggingface.co/kelvi23/DistilBERT-Reconciler) – **3.2M labeled post-trade break descriptions and resolution actions** – but using the original `bert-base-uncased` architecture.

The goal is to provide a performance benchmark against which lightweight and distilled models can be evaluated.

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## Intended Use

Automated classification of reconciliation exceptions in fixed-income settlement workflows (CUSIP/ISIN).  
The model will output a `label_id` mapped to a human-readable root-cause and recommended resolution step.

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## Planned Training Details

* **Base**: `bert-base-uncased`
* **Epochs**: TBD (expected 3–5)
* **Learning Rate**: TBD (expected ~3e-5)
* **Max Length**: 256
* **Dataset**: Proprietary + ISO 20022-derived corpus (post-trade break descriptions)
* **Split**: 80% train / 20% hold-out
* **Evaluation Metrics**: Accuracy, Micro-F1, Macro-F1

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## Expected Benchmark

| Model                   | Accuracy | Micro-F1 | Macro-F1 |
|-------------------------|----------|----------|----------|
| DistilBERT-Reconciler   | 0.88     | 0.88     | 0.85     |
| **BERT-Breaks-v0**      | (Coming) | (Coming) | (Coming) |

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## Limitations & Bias

* Labels are derived from North-American corporate-bond desks (2019–2025).  
* May under-perform on equities, repos, or non-USD instruments without re-training.  
* Baseline model is expected to have **larger inference latency** compared to distilled variants.

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## Citation

> Musodza, K. (2025). Bond Settlement Automated Exception Handling and Reconciliation. Zenodo. https://doi.org/10.5281/zenodo.16828730
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## Related Models

* [`DistilBERT-Reconciler`](https://huggingface.co/kelvi23/DistilBERT-Reconciler) – Fine-tuned lightweight alternative.
* [`Streaming-fail-forecaster`](https://huggingface.co/kelvi23/Streaming-fail-forecaster) – Next-day settlement-fail forecasting models.
* [`settlement-stress-flagger-v1`](https://huggingface.co/kelvi23/settlement-stress-flagger-v1) – CUSIP-level stress-event classifier.