ResNet-152 (ImageNet)

Training compute

10¹⁹ FLOP

Parameters

60.2M

Published

Dec 10, 2015

ResNet-152 (ImageNet) is an AI model developed by Microsoft (United States), first published in December 2015. It works in the vision domain, on tasks such as image classification.

Training it took an estimated 10¹⁹ FLOP of compute (estimation method: operation counting,third-party estimation). The model has 60,200,000 parameters. It was trained on roughly 1.3M datapoints.

The reference paper has 228,517 citations. Epoch AI rates the confidence of this record as confident.

Full record

Organization: Microsoft
Country of organization: United States
Domain: Vision
Task: Image classification
Training compute: 10¹⁹ FLOP
Compute estimation method: Operation counting, Third-party estimation
Parameters: 60,200,000
Dataset size: 1.3M
Numerical format: FP32
Citations: 228,517
Epoch confidence: Confident