| --- |
| tags: |
| - tabular |
| - tabpfn |
| - bankruptcy-prediction |
| - financial-distress |
| - finance |
| datasets: |
| - sebastiantomczak10/v4-group-corporate-bankruptcy |
| --- |
| |
| # V4FinBench TabPFN Checkpoints |
|
|
| Finetuned [TabPFN v2](https://github.com/PriorLabs/TabPFN) checkpoints for |
| corporate financial distress prediction on V4FinBench. We release one |
| checkpoint per prediction horizon (h = 0, …, 5), each trained with the |
| **prototype-undersampling** context-construction strategy that performs |
| best in our experiments. |
|
|
| - **Dataset (Kaggle):** <https://www.kaggle.com/datasets/sebastiantomczak10/v4-group-corporate-bankruptcy/data> |
| - **Code (GitHub):** <https://github.com/genwro-ai/V4FinBench> |
|
|
| ## What's in this repo |
|
|
| Six TabPFN v2 checkpoints, one per V4FinBench horizon task: |
|
|
| | File | Horizon | Description | |
| |---|---|---| |
| | `tabpfn_h0.ckpt` | h = 0 | Current-year financial distress | |
| | `tabpfn_h1.ckpt` | h = 1 | One-year-ahead distress | |
| | `tabpfn_h2.ckpt` | h = 2 | Two-year-ahead distress | |
| | `tabpfn_h3.ckpt` | h = 3 | Three-year-ahead distress | |
| | `tabpfn_h4.ckpt` | h = 4 | Four-year-ahead distress | |
| | `tabpfn_h5.ckpt` | h = 5 | Five-year-ahead distress | |
|
|
| Each checkpoint is the per-horizon model selected by maximizing |
| $F_1$-score on the validation fold, finetuned from the pretrained |
| TabPFN v2 base with imbalance-aware in-context construction (clustered |
| majority prototypes paired with all minority examples). |
| |
| ## Loading checkpoints |
| |
| See the V4FinBench code repository for loading and inference: |
| <https://github.com/genwro-ai/V4FinBench> |
| |
| ## Training details |
| |
| - **Base model:** TabPFN v2 |
| - **Finetuning:** Adam, 10 epochs, learning rate 5e-6, batch size 1024, |
| inference context size 10,000. |
| - **Context construction:** prototype undersampling — for each context, |
| all minority-class examples are retained; majority-class examples are |
| selected by clustering with MiniBatchKMeans and keeping the real |
| observation closest to each centroid, until |
| $N_{\text{min}} / N_{\text{maj}} = 0.3$. |
| - **Hardware:** single NVIDIA A100 GPU per run. |
| - **Folds:** 5-fold company-grouped, country-stratified |
| cross-validation. The released checkpoint per horizon is the |
| best-performing fold by validation $F_1$. |
|
|
| Full configuration, evaluation protocol, and per-fold results are |
| documented in the paper and in the GitHub code repository. |
|
|
| ## Scope of this release |
|
|
| This repository contains a curated subset of the checkpoints produced |
| in the paper. The full reference experiments produce 90 checkpoints |
| total (6 horizons × 5 folds × 3 context-construction strategies); |
| reproducing them is fully supported by the released folds and training |
| code in the GitHub repository. |
|
|
| ## Intended use |
|
|
| These checkpoints are intended for: |
|
|
| - Benchmarking corporate financial-distress prediction methods on |
| V4FinBench under the released evaluation protocol. |
| - Research on tabular foundation models, in-context learning under |
| severe class imbalance, and cross-dataset transfer in financial |
| prediction (e.g., the American Bankruptcy Dataset transfer experiment |
| in the paper). |
|
|
| ## Limitations and responsible use |
|
|
| - These checkpoints are **research artifacts**, not production |
| risk-scoring models. They are not intended for, and should not be |
| used to make, individual credit decisions, supplier-risk decisions, |
| or any other automated decisions about specific companies without |
| additional jurisdiction-specific validation, fairness analysis, and |
| human oversight. |
| - V4FinBench labels capture composite financial distress (joint |
| deterioration in solvency, profitability, and liquidity), not |
| formal legal bankruptcy filings. Predictions reflect the operational |
| distress definition in the paper and may not generalize to other |
| distress or bankruptcy definitions. |
| - Training data covers four Central European economies (Poland, |
| Hungary, Czech Republic, Slovakia) over 2006–2021. Performance on |
| other economies, accounting standards, or time periods is not |
| guaranteed; see the cross-dataset transfer analysis in the paper for |
| one external evaluation point. |
|
|
| ## License |
|
|
| These checkpoints are derivatives of TabPFN v2 and are released under |
| the TabPFN license included in this repository (`LICENSE`). Please |
| review the license terms before use. |
|
|
| ## Citation |
|
|
| A citation entry will be added once the preprint is available. |
