MACHINE LEARNING BERKELEY The good PRE-TRAINED ON ●' Nice image representations EVALUATION MODEL ACCURACY LARSLAE CIFAR-10 ResNet-15210 94.0 ● SOTA on semi-supervised classification Linear Probe SimCLR12 95.3 o Task:classification with limited labeled samples iGPT-L 32x32 96.3 CIFAR-100 ResNet-152 78.0 0 Model:linear classifer on iGPT representations Linear Probe SimCLR 80.2 o Competitive results with a naive method iGPT-L32x32 82.8 lots of compute ● Nice image generations o Effective at modeling visual information The good ● Nice image representations ● SOTA on semi-supervised classification ○ Task: classification with limited labeled samples ○ Model: linear classifier on iGPT representations ○ Competitive results with a naive method + lots of compute ● Nice image generations ○ Effective at modeling visual information