I was going through this paper and I understood the concept of the Meta-learning framework and using a few-shot technique. But when I tried to interpret the results in "Table 1: Results on the Omniglot dataset", I couldn't understand the column "Fine Tune".
- Is this "Fine Tune" the same as hyperparameter tuning?
- If so, shouldn't the accuracy be higher when fine-tune is yes as compared to when not fine-tuned?
or am I misinterpreting something?