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diff --git a/models/bvlc_alexnet/readme.md b/models/bvlc_alexnet/readme.md new file mode 100644 index 00000000..20c393ff --- /dev/null +++ b/models/bvlc_alexnet/readme.md @@ -0,0 +1,25 @@ +--- +name: BVLC AlexNet Model +caffemodel: bvlc_alexnet.caffemodel +caffemodel_url: http://dl.caffe.berkeleyvision.org/bvlc_alexnet.caffemodel +license: non-commercial +sha1: 9116a64c0fbe4459d18f4bb6b56d647b63920377 +caffe_commit: 709dc15af4a06bebda027c1eb2b3f3e3375d5077 +--- + +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. + +Differences: +- not training with the relighting data-augmentation; +- initializing non-zero biases to 0.1 instead of 1 (found necessary for training, as initialization to 1 gave flat loss). + +The bundled model is the iteration 360,000 snapshot. +The best validation performance during training was iteration 358,000 with validation accuracy 57.258% and loss 1.83948. +This model obtains a top-1 accuracy 57.1% and a top-5 accuracy 80.2% 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.) + +## 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. |