update comparisons

README.md

@@ -60,6 +60,8 @@ model = torch.load(model_name)
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 # Top-1 Accuracy Comparisons
+I finetuned the existing models on either 299x299, 304x304, 320x320, or 384x384 resolution, depending on the input size used during pretraining and the VRAM usage.
+
 `efficientnet_b3_pruned` achieved the second highest top-1 accuracy as well as the highest epoch-1 training accuracy on my task, out of all previous EfficientNet models my 24 GB VRAM RTX 3090 could handle.
 
 I will publish the detailed report in another model repository, including the link to the GVNS benchmarks.