Designovel’s system description for Fashion-IQ challenge 2019
Table 2: Evaluation results (average recall, %) on Fashion-IQ dataset
['-', 'Validation', 'Test']
We began with the baseline in which we set the same learning rate 5e-5 on all modules, and gradually adjusted the settings by lowering the learning rate of text and image encoder to 5e-6 (as suggested in [Nam]), applying data augmentation on the training data and ensembling several trained models from different runs. For model ensembling, we first calculated similarity scores with each sub-model separately and then simply averaged these scores.