name | caffemodel | caffemodel_url | license | sha1 | caffe_commit |
---|---|---|---|---|---|
BVLC CaffeNet Model |
bvlc_reference_caffenet.caffemodel |
non-commercial |
4c8d77deb20ea792f84eb5e6d0a11ca0a8660a46 |
709dc15af4a06bebda027c1eb2b3f3e3375d5077 |
This model is the result of following the Caffe ImageNet model training instructions. It is a replication of the model described in the AlexNet publication with some differences:
- not training with the relighting data-augmentation;
- the order of pooling and normalization layers is switched (in CaffeNet, pooling is done before normalization).
This model is snapshot of iteration 310,000. The best validation performance during training was iteration 313,000 with validation accuracy 57.412% and loss 1.82328. This model obtains a top-1 accuracy 57.4% and a top-5 accuracy 80.4% on the validation set, using just the center crop. (Using the average of 10 crops, (4 + 1 center) * 2 mirror, should obtain a bit higher accuracy still.)
The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access: "Researcher shall use the Database only for non-commercial research and educational purposes." Accordingly, this model is distributed under a non-commercial license.