run_cifar10_based_unsupervised_experiments.sh

#!/bin/bash

# Train a RotNet (with a NIN architecture of 4 conv. blocks) on training images of CIFAR10.
CUDA_VISIBLE_DEVICES=0 python main.py --exp=CIFAR10_RotNet_NIN4blocks

# Train & evaluate an object classifier (for the CIFAR10 task) with convolutional 
# layers on the feature maps of the 2nd conv. block of the RotNet model trained above.
CUDA_VISIBLE_DEVICES=0 python main.py --exp=CIFAR10_ConvClassifier_on_RotNet_NIN4blocks_Conv2_feats

# Train & evaluate an object classifier (for the CIFAR10 task) with 3 fully connected layers 
# on the feature maps of the 2nd conv. block of the above RotNet model trained above.
CUDA_VISIBLE_DEVICES=0 python main.py --exp=CIFAR10_MultLayerClassifier_on_RotNet_NIN4blocks_Conv2_feats