bert-breaks-v0

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 – 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

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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 – Fine-tuned lightweight alternative.
• Streaming-fail-forecaster – Next-day settlement-fail forecasting models.
• settlement-stress-flagger-v1 – CUSIP-level stress-event classifier.