Some questions about reproducibility

[JennyVanessa]

Dear author,

As mentioned in the supplementary materials, the hyperparameters were set as follows:

To train our TANet, we used Microsoft's neural network intelligence (NNI) tuning tool, where the learning rate search space from L1 to L6 was set as [0.000001, 0.0000001, 0.0000003], without any decay rate strategy. Specifically, we set the input size to 40 and the number of training epochs to 200. We used 224 × 224 crops from 256 × 256 fixed images as input.

However, achieving the desired training results in a single step with this particular combination of hyperparameters has proven to be challenging due to the absence of a decay rate strategy. I wonder if you performed multiple training steps, manually adjusting the learning rate to obtain the best results. For example, training for a certain number of epochs with one set of hyperparameters and then building upon that by training further, ensuring the total number of training epochs reaches 200, rather than directly training for 200 epochs using a specific set of hyperparameters. If this is the case, how can the ablation experiment be performed to ensure the accuracy of the experiment? Additionally, the provision of random seeds was not mentioned.

I would greatly appreciate your insights and guidance on this matter.

Warm regards,

Vanessa