Here are the latest pretrained weights on ImageNet dataset.
In this version, we fixed an unintentional bug in the model, where the 1x1 convs had paddings of 1,
this is now taken care of and new weightsand models are provided.
m2 variants:
| Method | #Params | ImageNet | ImageNet-Real-Labels |
|---|---|---|---|
| simplenetv1_9m_m2(36.3 MB) | 9.5m | 74.23/91.748 | 81.22/94.756 |
| simplenetv1_5m_m2(22 MB) | 5.7m | 72.03/90.324 | 79.328/93.714 |
| simplenetv1_small_m2_075(12.6 MB) | 3m | 68.506/88.15 | 76.283/92.02 |
| simplenetv1_small_m2_05(5.78 MB) | 1.5m | 61.67/83.488 | 69.31/ 88.195 |
m1 variants:
| Method | #Params | ImageNet | ImageNet-Real-Labels |
|---|---|---|---|
| simplenetv1_9m_m1(36.3 MB) | 9.5m | 73.792/91.486 | 81.196/94.512 |
| simplenetv1_5m_m1(22 MB) | 5.7m | 71.548/89.94 | 79.076/93.36 |
| simplenetv1_small_m1_075(12.6 MB) | 3m | 67.784/87.718 | 75.448/91.69 |
| simplenetv1_small_m1_05(5.78 MB) | 1.5m | 61.122/82.988 | 68.58/87.64 |
Note1:
some of these weights are achieved from finetuning the previous weights to shorten the training time
some others are trained from scratch.