Fine-tuning a model with the Trainer API - Hugging Face Course
It says on the above link:
As you can see, predictions is a two-dimensional array with shape 408 x 2 (408 being the number of elements in the dataset we used). Those are the logits for each element of the dataset we passed to predict() (as you saw in the previous chapter, all Transformer models return logits). To transform them into predictions that we can compare to our labels, we need to take the index with the maximum value on the second axis:
what does it mean that we need to take the index with the maximum value on the second axis?
What two axes are we talking about?