Internal change.

PiperOrigin-RevId: 367679732

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs101_i160.yaml

-# ResNet-RS-101 ImageNet classification. 80.2% accuracy.
+# ResNet-RS-101 ImageNet classification. 80.2% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs101_i192.yaml

-# ResNet-RS-101 ImageNet classification. 81.3% top-5 accuracy.
+# ResNet-RS-101 ImageNet classification. 81.3% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs152_i192.yaml

-# ResNet-RS-152 ImageNet classification. 81.9% top-5 accuracy.
+# ResNet-RS-152 ImageNet classification. 81.9% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs152_i224.yaml

-# ResNet-RS-152 ImageNet classification. 82.5% top-5 accuracy.
+# ResNet-RS-152 ImageNet classification. 82.5% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs152_i256.yaml

-# ResNet-RS-152 ImageNet classification. 83.1% top-5 accuracy.
+# ResNet-RS-152 ImageNet classification. 83.1% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs200_i256.yaml

-# ResNet-RS-200 ImageNet classification. 83.5% top-5 accuracy.
+# ResNet-RS-200 ImageNet classification. 83.5% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs270_i256.yaml

-# ResNet-RS-270 ImageNet classification. 83.6% top-5 accuracy.
+# ResNet-RS-270 ImageNet classification. 83.6% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs350_i256.yaml

-# ResNet-RS-350 ImageNet classification. 83.7% top-5 accuracy.
+# ResNet-RS-350 ImageNet classification. 83.7% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs350_i320.yaml

-# ResNet-RS-350 ImageNet classification. 84.2% top-5 accuracy.
+# ResNet-RS-350 ImageNet classification. 84.2% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'

official/vision/beta/configs/experiments/image_classification/imagenet_resnetrs50_i160.yaml

-# ResNet-RS-50 ImageNet classification. 79.1% top-5 accuracy.
+# ResNet-RS-50 ImageNet classification. 79.1% top-1 accuracy.
 runtime:
   distribution_strategy: 'tpu'
   mixed_precision_dtype: 'bfloat16'