  In this paper, we perform a thorough sensitivity analysis on state-of-the-art
image captioning approaches using two different architectures: CNN+LSTM and
CNN+Transformer. Experiments were carried out using the Flickr8k dataset. The
biggest takeaway from the experiments is that fine-tuning the CNN encoder
outperforms the baseline and all other experiments carried out for both
architectures.
