Best way for adding the model and the tokenizer as hyper-parameters in RayTune
I am using the Trainer class and the hyperparameter evaluation with RayTune for fine-tunning a classification model. I already have as parameters the learning rate, the warm-up, the number of epochs, the batch size, and the weight decay. Now I want to add as hyperpameters the “model”, discerning between the cased and uncased and between large and base.I have no problems in create different version of the models and selecting the best one in the model_init function. However, as the datasets are provided as input in the transformers.Trainer class (and they have already the texts tokenised) I am not sure what is the best approach to follow.Any suggestion would be appreciate