Codesota · Models · ResNet-152Microsoft3 results · 2 benchmarks
Model card

ResNet-152.

Microsoftopen-source60M paramsCNNMIT

78.6% on ImageNet (10-crop). Deep residual network.

§ 02 · Benchmarks

Every benchmark ResNet-152 has a recorded score for.

#BenchmarkArea · TaskMetricValueRankDateSource
01ImageNetComputer Vision · Image Classificationtop-5-accuracy96.4%#2/52015-01-01source ↗
02ImageNet-1KComputer Vision · Image Classificationaccuracy80.6%#12/26source ↗
03ImageNet-1KComputer Vision · Image Classificationtop-1-accuracy78.6%#18/20source ↗
Rank column shows this model’s position vs all other models scored on the same benchmark + metric (competitors after the slash). #1 in red means current SOTA. Sorted by rank, then newest result.
§ 03 · Strengths by area

Where ResNet-152 actually performs.

Computer Vision
2
benchmarks
avg rank #10.7
§ 04 · Papers

1 paper with results for ResNet-152.

  1. 2015-12-10· 1 result

    Deep Residual Learning for Image Recognition

§ 05 · Related models

Other Microsoft models scored on Codesota.

RAD-DINO
2 results · 1 SOTA
NaturalSpeech 3
~500M params · 1 result · 1 SOTA
Swin Transformer V2 Large
197M params · 1 result · 1 SOTA
WavLM Large (SV)
316M params · 1 result · 1 SOTA
ResNet-50
25M params · 3 results
DeBERTa-v3-large
304M params · 2 results
Florence-2-Large
2 results
KOSMOS-2.5
2 results
§ 06 · Sources & freshness

Where these numbers come from.

codesota-editorial
1
result
pwc-dump
1
result
microsoft-research
1
result
1 of 3 rows marked verified.