Statement of originality
(a) Hyperparameters for the language models.
['[EMPTY]', 'No transfer', 'Same captions', 'Different captions', 'General text']
-Ch4F2sf4 -Ch4F5sf4 -Ch4F11sf3 This process was performed twice for each hyperparameter combination and the average perplexity or WMD resulting from the two independent train and generation sessions was used as a score for the hyperparameter combination. This makes the score more robust than if the model was only trained and evaluated once. As a reminder, the model, whose purpose is to predict the fitness of a given hyperparameter combination, is a random forest and was initialised using 32 random hyperparameter combinations paired with their evaluated fitness (the perplexity or WMD). The hyperparameter combinations were then optimised by exploring a sequence of 64 candidate hyperparameters that the model suggests will maximise the expected improvement in fitness. Again, the ‘no transfer’ model’s hyperparameters were copied over from those of Chapter 3.