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---
name: BVLC CaffeNet Model
caffemodel: bvlc_reference_caffenet.caffemodel
caffemodel_url: http://dl.caffe.berkeleyvision.org/bvlc_reference_caffenet.caffemodel
license: non-commercial
sha1: 4c8d77deb20ea792f84eb5e6d0a11ca0a8660a46
caffe_commit: 709dc15af4a06bebda027c1eb2b3f3e3375d5077
---
This model is the result of following the Caffe [instructions](http://caffe.berkeleyvision.org/gathered/examples/imagenet.html) on training an ImageNet model.
This model is a replication of the model described in the [AlexNet](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) 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.)
## License
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.
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