The similar instances are denoted by a label y = 1 whereas the dissimilar pairs are represented by y = 0.
the loss function has the following form: Each term is expressed by: This loss function measures how well the model learns to encode similar transformations such that analogous pairs are mutually close and form an analogical parallelogram in the embedding space, while pushing dissimilar transformations apart.