Pay Attention to MLPs

Benchmark Model Rank Results
image-classification-on-imagenetgMLP-B#601Top 1 Accuracy: 81.6%Number of params: 73MGFLOPs: 31.6
natural-language-inference-on-multinligMLP-large#22Matched: 86.2Mismatched: 86.5
question-answering-on-squad20gMLP-large#26F1: 78.3
sentiment-analysis-on-sst-2-binarygMLP-large#29Accuracy: 94.8