Comments (3)
Hi,
Without the pretrained model, you have to increase the learning rate for effective training. However, a pretrained model is important for small date sets to avoid overfitting.
from softtriple.
Hi,thanks for your best contribution
one of your paper's contribution is propose the softTriple loss, so if you or not try some other NN frameworks with softTriple loss and compare the performance
from softtriple.
We tried it on different neural networks but reported the performance on Inception for a fair comparison.
from softtriple.
Related Issues (16)
- proof of proposition1 HOT 1
- centers = F.normalize(self.fc, p=2, dim=0) what is its purpose? HOT 1
- proposition1 HOT 1
- The BatchNorm layers are not completely frozen HOT 1
- can you explain the recall@k? HOT 2
- pretrained models HOT 2
- out of memory error HOT 4
- softtriploss param HOT 1
- Code and Paper don't seem to match... HOT 2
- Out of Memory error when training on big number of classes HOT 2
- Clarification on gamma and lambda HOT 2
- MemoryError: Unable to allocate 113. GiB for an array with shape (122994, 122994) and data type float64 HOT 1
- loss is nan HOT 7
- Question - data with unit length HOT 1
- Centers
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from softtriple.