<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Posts on John Paulett</title><link>https://www.johnpaulett.com/posts/</link><description>Recent content in Posts on John Paulett</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 07 Jan 2025 18:00:00 -0500</lastBuildDate><atom:link href="https://www.johnpaulett.com/posts/index.xml" rel="self" type="application/rss+xml"/><item><title>ModernBERT in Radiology Part 3: Fine-tuning a Classifier</title><link>https://www.johnpaulett.com/2025/modernbert-radiology-fine-tuning-classifier/</link><pubDate>Tue, 07 Jan 2025 18:00:00 -0500</pubDate><guid>https://www.johnpaulett.com/2025/modernbert-radiology-fine-tuning-classifier/</guid><description>&lt;p>In Part 3 of the ModernBERT in Radiology series, we will fine-tune a ModernBERT Classifier to predict the UMLS CUIs given a radiology report. It will combine our fine-tuning from &lt;a href="https://www.johnpaulett.com/2025/modernbert-radiology-fine-tuning-masked-langage-model/">Part 2&lt;/a> to produce a better classifier than the simple scikit-learn Logistic Regression from &lt;a href="https://www.johnpaulett.com/2025/modernbert-radiology-hidden-states-classifier/">Part 1&lt;/a>.&lt;/p>
&lt;p>You can follow along with the associated &lt;a href="https://colab.research.google.com/drive/11hpCvNb4g65Igcmz1ePyuqdNmWwYwj4g?usp=sharing">Colab Notebook for Part 3&lt;/a>🔥!&lt;/p>
&lt;h2 id="the-modernbert-in-radiology-series">The ModernBERT in Radiology Series&lt;/h2>
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&lt;p>Part 1: &lt;a href="https://www.johnpaulett.com/2025/modernbert-radiology-hidden-states-classifier/">Simple Classifier using Hidden States&lt;/a>.&lt;/p>
&lt;p>Build a multi-label classification using a simple scikit-learn Logistic Regression model on top of the pre-trained ModernBERT body.&lt;/p></description></item><item><title>ModernBERT in Radiology Part 2: Fine Tuning a Masked Language Model (MLM)</title><link>https://www.johnpaulett.com/2025/modernbert-radiology-fine-tuning-masked-langage-model/</link><pubDate>Mon, 06 Jan 2025 17:00:00 -0500</pubDate><guid>https://www.johnpaulett.com/2025/modernbert-radiology-fine-tuning-masked-langage-model/</guid><description>&lt;p>In Part 2 of the ModernBERT in Radiology series, we will fine-tune ModernBERT against the ROCOv2 dataset for Radiology for the Masked Language Model task so that given an input of &lt;code>ninth [MASK] fracture&lt;/code> the model would predict &lt;code>ninth rib fracture&lt;/code>.&lt;/p>
&lt;p>You can follow along with the associated &lt;a href="https://colab.research.google.com/drive/1pARD1JpZR9qQDdtqFSWYdz2vuEJ04scB?usp=sharing">Colab Notebook for Part 2&lt;/a>🔥!&lt;/p>
&lt;h2 id="the-modernbert-in-radiology-series">The ModernBERT in Radiology Series&lt;/h2>
&lt;ul>
&lt;li>
&lt;p>Part 1: &lt;a href="https://www.johnpaulett.com/2025/modernbert-radiology-hidden-states-classifier/">Simple Classifier using Hidden States&lt;/a>.&lt;/p>
&lt;p>Build a multi-label classification using a simple scikit-learn Logistic Regression model on top of the pre-trained ModernBERT body.&lt;/p></description></item><item><title>ModernBERT in Radiology Part 1: Simple Classifier using Hidden States</title><link>https://www.johnpaulett.com/2025/modernbert-radiology-hidden-states-classifier/</link><pubDate>Sun, 05 Jan 2025 07:00:00 -0500</pubDate><guid>https://www.johnpaulett.com/2025/modernbert-radiology-hidden-states-classifier/</guid><description>&lt;p>In Part 1 of the ModernBERT in Radiology series, we will explore ModernBERT and the ROCOv2 dataset for Radiology. We build a multi-label classifier using a simple Logistic Regression model on top of the pre-trained ModernBERT body.&lt;/p>
&lt;p>You can follow along with the associated &lt;a href="https://colab.research.google.com/drive/1sfRbr-nE6LtJmgNFtOYstZ-YbIQ-DeMb?usp=sharing">Colab Notebook for Part 1&lt;/a>🔥!&lt;/p>
&lt;h2 id="the-modernbert-in-radiology-series">The ModernBERT in Radiology Series&lt;/h2>
&lt;ul>
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&lt;p>Part 1: Simple Classifier using Hidden States. &lt;strong>👈 This Post&lt;/strong>&lt;/p>
&lt;p>Build a multi-label classification using a simple scikit-learn Logistic Regression model on top of the pre-trained ModernBERT body.&lt;/p></description></item><item><title>And we're back</title><link>https://www.johnpaulett.com/2024/and-we-are-back/</link><pubDate>Sun, 22 Dec 2024 18:39:58 -0500</pubDate><guid>https://www.johnpaulett.com/2024/and-we-are-back/</guid><description>&lt;p>After setting up by bluesky to use a custom &lt;a href="https://bsky.app/profile/johnpaulett.com">@johnpaulett&lt;/a> handle (learn how set up &lt;a href="https://bsky.social/about/blog/4-28-2023-domain-handle-tutorial">your own domain handle&lt;/a>), a friend pointed out my website was dead! Apparently sometime in the past 15 years (🤯) without touching it, my custom Django blog app written in Django v1.3 got disconnected from its Heroku Postgres.&lt;/p>
&lt;p>Figured I should simplify the setup, since there is no need to have a database and app server (that costs $10/mo) to serve a blog that probably gets a few pageviews a month, a static generated site will work.&lt;/p></description></item></channel></rss>