<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>SFT on Rajat Patel</title><link>https://rajathpatel23.github.io/tags/sft/</link><description>Recent content in SFT on Rajat Patel</description><generator>Hugo -- 0.167.0</generator><language>en-us</language><managingEditor>rpatel12@umbc.edu (Rajat Patel)</managingEditor><webMaster>rpatel12@umbc.edu (Rajat Patel)</webMaster><lastBuildDate>Sun, 27 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://rajathpatel23.github.io/tags/sft/index.xml" rel="self" type="application/rss+xml"/><item><title>Pretrain, SFT, then the DPO run that held</title><link>https://rajathpatel23.github.io/posts/tiny-shakespeare-sft-dpo/</link><pubDate>Sun, 27 Sep 2026 00:00:00 +0000</pubDate><author>rpatel12@umbc.edu (Rajat Patel)</author><guid>https://rajathpatel23.github.io/posts/tiny-shakespeare-sft-dpo/</guid><description>A 15M-parameter model pretrained on tiny-shakespeare, fine-tuned to stop after one line, then aligned with DPO. The same learning rate that worked for SFT broke generation. A tenfold cut fixed it.</description></item></channel></rss>