You fit an unregularized logistic-regression probe on 4,096-dimensional embeddings from a frozen model, with 1,500 labeled examples and full-batch gradient descent at a fixed learning rate.

Training accuracy reaches 100% early, the loss keeps creeping toward zero, and the weight norm keeps growing, so the convergence check never fires.