Because the OCELOT database is smaller than the OMDB, we chose to fine-tune models trained on the OMDB with data from OCELOT. The best performing model of each of the three runs as described above, defined by having the lowest validation loss, was chosen for fine-tuning. Hyperparameter tuning was also performed before fine-tuning for parameters such as the number of epochs, the batch size, the learning rate, and the dropout rate, using the framework described in Section 3.1.3. The results of the hyperparameter search are shown in Table .1.3.