Instructions to use yunicro/MiDM-9B-q35-e1-bx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use yunicro/MiDM-9B-q35-e1-bx with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
v0.2.2 report and financial validation; unchanged model weights
Browse files- README.md +4 -0
- financial_validation/v0.2.2/README.md +15 -0
- financial_validation/v0.2.2/evaluation.json +132 -0
README.md
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@@ -8,6 +8,10 @@ tags: [midm, decision-model, typed-decisions, pointer-head, lora, qlora]
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# MiDM-9B-q35-e1-bx
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## v0.2.1 benchmark and architecture analysis
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Documentation update; this repository's existing weights and inference code are unchanged. [Full benchmark atlas](benchmarks/v0.2.1/README.md) · [GitHub release](https://github.com/YeoHoonYun/midm-decision-models/releases/tag/v0.2.1) · [Version DOI](https://doi.org/10.5281/zenodo.23164651).
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# MiDM-9B-q35-e1-bx
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## v0.2.2 financial validation and report update
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**Documentation only; weights remain v0.2.0. No improved financial checkpoint is released.** [ScenarioView report](https://yeohoonyun.github.io/midm-decision-models/) · [Validation notes](financial_validation/v0.2.2/README.md). MiDM baseline action accuracy was 54.37%; tested residual variants did not justify replacement. These are reused retrospective KOSPI decisions, not live signals or general benchmark gains.
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## v0.2.1 benchmark and architecture analysis
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Documentation update; this repository's existing weights and inference code are unchanged. [Full benchmark atlas](benchmarks/v0.2.1/README.md) · [GitHub release](https://github.com/YeoHoonYun/midm-decision-models/releases/tag/v0.2.1) · [Version DOI](https://doi.org/10.5281/zenodo.23164651).
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financial_validation/v0.2.2/README.md
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# v0.2.2 — ScenarioView report and financial validation
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Documentation/report release dated 2026-10-07. Model weights, tokenizer and loader are unchanged from v0.2.0; this is NOT an improved-accuracy model release.
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- Publishes a mobile-friendly ScenarioView report using the previous local report layout styles and section order.
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- Includes public macro observations with observation dates and source attribution, RT definitions, aggregate action metrics, and section-level provenance.
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- Frozen MiDM action accuracy: 54.37%; B3+MiDM stacking: 50.93%; development-selected horizon/position residual: 47.49%. No candidate promoted.
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- Evaluation: KOSPI, 2024-01-02 to 2026-08-20, 756 hypothetical decisions / 129 sampled dates, previously seen retrospective data; not independent trades or portfolio returns.
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- No validated economic leading/coincident/lagging status. New prompt context packs are prepared locally but have not been inference-tested.
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- No private source prices, per-date predictions, generated private narratives, checkpoint files or credentials published.
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- The report is issued today but does not contain a freshly inferred today-market signal. No automatic daily schedule is configured.
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Report: https://yeohoonyun.github.io/midm-decision-models/
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The prior Zenodo DOI continues to refer to v0.2.1; no new Zenodo deposit is claimed.
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financial_validation/v0.2.2/evaluation.json
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@@ -0,0 +1,132 @@
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{
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"documentation_version": "0.2.2",
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"weights_version": "0.2.0",
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"report_date": "2026-10-07",
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"market": "KOSPI",
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"evaluation_period": [
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"2024-01-02",
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"2026-08-20"
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],
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"unique_dates": 129,
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"hypothetical_decisions": 756,
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"robust_heads": {
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"raw_MiDM": {
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"n": 756,
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"accuracy": 0.5436507936507936,
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"balanced_accuracy": 0.4923740904551291,
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"utility_regret_bp": 202.6737499060071,
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"long_fraction": 0.8716931216931217
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},
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"always_long": {
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"n": 756,
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"accuracy": 0.5687830687830688,
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"balanced_accuracy": 0.5,
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"utility_regret_bp": 200.93760231754584,
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"long_fraction": 1.0
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},
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"numeric_residual": {
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"n": 756,
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"accuracy": 0.4880952380952381,
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"balanced_accuracy": 0.4828577543158796,
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"utility_regret_bp": 254.72531339383275,
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"long_fraction": 0.5357142857142857
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},
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"horizon_residual": {
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"n": 756,
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"accuracy": 0.4748677248677249,
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"balanced_accuracy": 0.47753602511057214,
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"utility_regret_bp": 264.7359928251329,
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"long_fraction": 0.4775132275132275
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},
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"latent_residual": {
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"n": 756,
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"accuracy": 0.5052910052910053,
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"balanced_accuracy": 0.4998287915537167,
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"utility_regret_bp": 246.82435842755385,
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"long_fraction": 0.5396825396825397
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},
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"random_features": {
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"n": 756,
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"accuracy": 0.48412698412698413,
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"balanced_accuracy": 0.5172064488514767,
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"utility_regret_bp": 237.01935194499768,
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"long_fraction": 0.2619047619047619
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}
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},
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"fusion": {
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"raw_MiDM": {
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"n": 756,
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"accuracy": 0.5436507936507936,
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"balanced_accuracy": 0.4923740904551291,
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"long_fraction": 0.8716931216931217,
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"utility_regret_bp": 202.6737499060071
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},
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"B3_logistic": {
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"n": 756,
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"accuracy": 0.5066137566137566,
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"balanced_accuracy": 0.4972820659152518,
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"long_fraction": 0.5674603174603174,
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"utility_regret_bp": 263.8134549025119
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},
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"MiDM_calibrated": {
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"n": 756,
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"accuracy": 0.548941798941799,
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"balanced_accuracy": 0.4951704950777571,
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"long_fraction": 0.8902116402116402,
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"utility_regret_bp": 201.03404296303668
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},
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"stacked": {
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"n": 756,
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"accuracy": 0.5092592592592593,
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"balanced_accuracy": 0.5010914538450564,
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"long_fraction": 0.5595238095238095,
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"utility_regret_bp": 260.755558602786
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},
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"mix_0": {
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"n": 756,
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"accuracy": 0.5066137566137566,
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"balanced_accuracy": 0.4972820659152518,
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"long_fraction": 0.5674603174603174,
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"utility_regret_bp": 263.8134549025119
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},
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"mix_0.25": {
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"n": 756,
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"accuracy": 0.5079365079365079,
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"balanced_accuracy": 0.49844485661292626,
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"long_fraction": 0.5687830687830688,
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"utility_regret_bp": 263.4556812103133
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},
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"mix_0.5": {
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"n": 756,
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"accuracy": 0.5079365079365079,
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"balanced_accuracy": 0.49844485661292626,
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"long_fraction": 0.5687830687830688,
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"utility_regret_bp": 263.4556812103133
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},
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"mix_0.75": {
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"n": 756,
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"accuracy": 0.5092592592592593,
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"balanced_accuracy": 0.4984947924097589,
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"long_fraction": 0.578042328042328,
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"utility_regret_bp": 263.84772576633515
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},
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"mix_1": {
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"n": 756,
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"accuracy": 0.548941798941799,
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"balanced_accuracy": 0.4951704950777571,
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"long_fraction": 0.8902116402116402,
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"utility_regret_bp": 201.03404296303668
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},
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"always_long": {
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| 121 |
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"n": 756,
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"accuracy": 0.5687830687830688,
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"balanced_accuracy": 0.5,
|
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"long_fraction": 1.0,
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| 125 |
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"utility_regret_bp": 200.93760231754584
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| 126 |
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}
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},
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"promotion": false,
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"private_rows_included": false,
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"scope": "Retrospective action decisions, not RT case accuracy or portfolio returns",
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"prompt_enrichment_inference": "not run"
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}
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