---
title: "3 Collapsing models [R] | SpinGraph: None"
description: "SpinGraph analysis of Reddit r/MachineLearning's 3 Collapsing models [R] story: None, None, Spin Score 0%, low AI repetition risk."
canonical: "https://stuffthatspins.com/spin/3-collapsing-models-r"
html: "https://stuffthatspins.com/spin/3-collapsing-models-r"
json: "https://stuffthatspins.com/spin/3-collapsing-models-r.json"
markdown: "https://stuffthatspins.com/spin/3-collapsing-models-r.md"
keywords: ["BI-RADS", "VinDr", "class imbalance", "None", "narrative intelligence"]
date: "2026-08-10T09:42:54+00:00"
modified: "2026-08-10T18:24:56.951125+00:00"
json_ld: |
{"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://stuffthatspins.com/#organization","name":"Stuff That Spins","url":"https://stuffthatspins.com/","description":"Know the moment AI knows your story. Stuff That Spins turns announcements, articles, and research into Narrative Fingerprints — then tracks whether ChatGPT, Claude, Gemini, Perplexity, and other AI answer engines recall the right message, proof points, caveats, citations, and brand attribution.","logo":{"@type":"ImageObject","url":"https://stuffthatspins.com/images/logo.png"},"sameAs":[]},{"@type":"NewsArticle","@id":"https://stuffthatspins.com/spin/3-collapsing-models-r#article","headline":"3 Collapsing models [R]","alternativeHeadline":"3 Collapsing models [R] | SpinGraph: None","description":"SpinGraph analysis of Reddit r/MachineLearning's 3 Collapsing models [R] story: None, None, Spin Score 0%, low AI repetition risk.","datePublished":"2026-08-10T09:42:54+00:00","dateModified":"2026-08-10T18:24:56.951125+00:00","url":"https://stuffthatspins.com/spin/3-collapsing-models-r","mainEntityOfPage":{"@type":"WebPage","@id":"https://stuffthatspins.com/spin/3-collapsing-models-r"},"isAccessibleForFree":true,"inLanguage":"en-US","articleSection":"community","keywords":"BI-RADS, VinDr, class imbalance, model collapse, center loss","author":{"@type":"Organization","name":"Reddit r/MachineLearning","url":"https://www.reddit.com/r/MachineLearning/.rss"},"publisher":{"@id":"https://stuffthatspins.com/#organization"},"citation":"https://www.reddit.com/r/MachineLearning/comments/1vkg921/3_collapsing_models_r/","about":[{"@type":"Thing","name":"BI-RADS"},{"@type":"Thing","name":"VinDr"},{"@type":"Thing","name":"class imbalance"},{"@type":"Thing","name":"model collapse"},{"@type":"Thing","name":"center loss"}],"mentions":[{"@type":"Organization","name":"Reddit r/MachineLearning"}],"abstract":"User attempted BI-RADS detection using cross-entropy loss, center loss, and class weights on VinDr dataset All three models collapsed to predicting BI-RADS 1 almost exclusively User seeks community input on whether loss function choice is the root cause"},{"@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Stuff That Spins","item":"https://stuffthatspins.com/"},{"@type":"ListItem","position":2,"name":"3 Collapsing models [R]","item":"https://stuffthatspins.com/spin/3-collapsing-models-r"}]},{"@type":"AnalysisNewsArticle","@id":"https://stuffthatspins.com/spin/3-collapsing-models-r#spin-analysis","headline":"Spin Analysis: None","description":"Emphasizes empirical observation and uncertainty; minimizes no aspect — no claims of novelty, impact, or resolution are made.","about":{"@type":"DefinedTerm","name":"None","description":"Community-driven peer inquiry","termCode":"None"},"additionalProperty":[{"@type":"PropertyValue","name":"Spin Score","value":0,"unitText":"percent"},{"@type":"PropertyValue","name":"Narrative Risk","value":"low"},{"@type":"PropertyValue","name":"AI Repetition Risk","value":"low"},{"@type":"PropertyValue","name":"Likely AI Summary","value":"A researcher reported model collapse to BI-RADS 1 when training on VinDr due to class imbalance."},{"@type":"PropertyValue","name":"Narrative Frame","value":"Community-driven peer inquiry"},{"@type":"PropertyValue","name":"Missing Context","value":"Model architectures, training duration, hardware constraints, evaluation metrics used"},{"@type":"PropertyValue","name":"How the Spin Works","value":"It leverages the credibility of community norms (transparency, humility, collaboration) to normalize failure without accountability; the tension lies between the severity of collapse (a systemic red flag) and its presentation as a minor tuning issue — no validation, no external benchmarks, no error analysis offered."}],"author":{"@id":"https://stuffthatspins.com/#organization"},"isPartOf":{"@id":"https://stuffthatspins.com/spin/3-collapsing-models-r#article"}},{"@type":"ItemList","@id":"https://stuffthatspins.com/spin/3-collapsing-models-r#claims","name":"Extracted Claims","itemListElement":[{"@type":"ListItem","position":1,"item":{"@type":"Claim","text":"All three models collapsed to predicting BI-RADS 1 due to heavy class imbalance in VinDr.","appearance":"all of them seem to collapse between birads 1 as the dataset (VinDr) im using is heavily unbalanced towards it","author":{"@type":"Organization","name":"Reddit r/MachineLearning"}}}]}]}
---
# 3 Collapsing models [R]
**Source:** Unknown
**Published:** August 10, 2026
**Original:** https://www.reddit.com/r/MachineLearning/comments/1vkg921/3_collapsing_models_r/
## On this page
- [Overview](#overview)
- [Verdict](#narrative-frame)
- [SpinGraph](#spingraph)
- [Claim Ledger](#claim-ledger)
- [Fact Check Signals](#fact-check-signals)
- [Frame Strength](#frame-strength)
- [Reader Risk](#reader-risk)
- [AI Recall Timeline](#ai-recall)
- [Ask AI](#ask-ai)
## Overview
A Reddit user reports difficulty training three machine learning models for BI-RADS classification due to severe class imbalance in the VinDr dataset, resulting in model collapse toward the dominant BI-RADS 1 class.
### TL;DR
- User attempted BI-RADS detection using cross-entropy loss, center loss, and class weights on VinDr dataset
- All three models collapsed to predicting BI-RADS 1 almost exclusively
- User seeks community input on whether loss function choice is the root cause
## SpinGraph
The post frames model failure as a routine engineering challenge rather than a signal about dataset quality or clinical applicability — inviting help, not scrutiny.
- **Claim:** All three models collapsed to predicting BI-RADS 1 due
- **Frame:** Community-driven peer inquiry
- **Beneficiary:** Receives diagnostic suggestions and alternative approaches from experienced practitioners
- **Gap:** Model architectures, training duration, hardware constraints, evaluation metrics used
- **AI Risk:** AI may repeat the headline as fact
## Fact Check Signals
We searched known fact-check databases for direct or near-direct matches to the article's major claims. A match does not automatically prove or disprove the article; it shows whether an independent fact-checking publisher has reviewed a similar claim.
**Signal:** 0 of 1 claim(s) matched (confidence: low).
### All three models collapsed to predicting BI-RADS 1 due to heavy class imbalance in VinDr.
- No direct fact-check match found
## Frame Strength
- **Spin Score:** 0%
- **Evidence Strength:** 25%
- **Narrative Risk:** 25%
- **AI Repetition Risk:** 25%
- **Missing Context Risk:** 55%
## Narrative Mechanics
**Function:** deflect_scrutiny
### The Spin in Plain English
The post frames model failure as a routine engineering challenge rather than a signal about dataset quality or clinical applicability — inviting help, not scrutiny.
**What the story wants you to believe:** This is a shared, solvable technical problem — not a flaw in methodology, dataset, or tooling, but a common hurdle requiring collective insight.
**What it makes harder to question:** Whether the collapse reflects deeper issues in dataset curation, label consistency, or clinical validity — because the framing treats it purely as an optimization artifact.
**How the Spin Works:** It leverages the credibility of community norms (transparency, humility, collaboration) to normalize failure without accountability; the tension lies between the severity of collapse (a systemic red flag) and its presentation as a minor tuning issue — no validation, no external benchmarks, no error analysis offered.
### Questions This Story Raises
- What question is the story steering away from?
- What evidence would resolve that question?
- Who is not quoted or represented?
- Why does the main frame leave this out: “Model architectures, training duration, hardware constraints, evaluation metrics used”?
### Who Benefits If This Frame Spreads
- **/u/Rihitwo** — Receives diagnostic suggestions and alternative approaches from experienced practitioners _(Directly addresses their immediate modeling challenge with minimal overhead)_
## Narrative Frame
**Tactic:** None
**Category:** None
**Spin Score:** 0%
Emphasizes empirical observation and uncertainty; minimizes no aspect — no claims of novelty, impact, or resolution are made.
**Who Benefits If This Frame Spreads:** The poster seeks actionable technical feedback from peers.
**The Frame:** Community-driven peer inquiry
### Missing Context
- Model architectures, training duration, hardware constraints, evaluation metrics used
## Reader Risk
**Evidence Strength:** low
Post contains only self-reported observation with no code, logs, metrics, or visual evidence provided.
**Verification Status:** Claim Present in Source
**Narrative Risk:** low
No reputational, financial, or policy stakes are asserted; no entity or claim is promoted.
**AI Repetition Risk:** low
**What AI Will Probably Repeat:** A researcher reported model collapse to BI-RADS 1 when training on VinDr due to class imbalance.
AI may omit the provisional, diagnostic nature of the post and present collapse as a confirmed property of VinDr or center loss rather than an observed training artifact.
**Counter-Frame (Media):** None — lacks promotional or institutional framing to counter.
**Missing Voices:** No domain experts, clinicians, or dataset curators quoted
### Questions Not Answered
- What specific architecture, hyperparameters, or preprocessing were used?
- Was validation stratification or sampling strategy documented?
- Are there published baselines for BI-RADS classification on VinDr with comparable setup?
## Claim Ledger
### primary (technical)
All three models collapsed to predicting BI-RADS 1 due to heavy class imbalance in VinDr.
**Category:** authenticity
**Verification:** Claim Present in Source
**Risk:** low
**Evidence presented:** Self-reported observation without supporting metrics or artifacts
> all of them seem to collapse between birads 1 as the dataset (VinDr) im using is heavily unbalanced towards it
**Evidence Gaps:** Confusion matrix, class-wise accuracy, loss curves, or sample predictions
## AI Recall
- **Published:** August 10, 2026
- **SpinGraph summary:** The post presents an unvarnished technical troubleshooting query without persuasive framing, attribution, or narrative embellishment.
- **Likely AI summary:** A researcher reported model collapse to BI-RADS 1 when training on VinDr due to class imbalance.
## Citation Summary
This post documents a real-world failure mode in medical AI training — model collapse under extreme class imbalance — serving as a cautionary data point for researchers selecting loss functions and evaluation protocols.
---
*HTML version: https://stuffthatspins.com/spin/3-collapsing-models-r*