Hi, It is a nice work! But I have a question about the training and testing settings.
For training, a task has one query data for each class (total 1 5 query data of a task) in the task. When testing, the performance of the model should not change much with the query number of each task. But my experiment shows that the performance will decrease a lot when there are more than one query data for each class in the task (>1 5 query data in a task) when testing. Specifically, the performance decreases to 11% when each test episode is formed by sampling 15 queries for each of 5 classes.
I am wondering if the model is overfitting for the specific setting: 1 query for each of 5 classes for a task.
Hi, It is a nice work! But I have a question about the training and testing settings.
For training, a task has one query data for each class (total 1 5 query data of a task) in the task. When testing, the performance of the model should not change much with the query number of each task. But my experiment shows that the performance will decrease a lot when there are more than one query data for each class in the task (>1 5 query data in a task) when testing. Specifically, the performance decreases to 11% when each test episode is formed by sampling 15 queries for each of 5 classes.
I am wondering if the model is overfitting for the specific setting: 1 query for each of 5 classes for a task.