I’m trying to implement a multi-label classification task, and currently my model has Embedding, GRU, 2x Linear layers.
I have padded the data, and its shape is (seq_len x batch) where seq_len is the longest sequence in that batch. Targets are multi-hot encoded as I’m using BCEWithLogitsLoss.
I have a weird issue that when using batch size > 1, I get much lower accuracy (0.3) when using batch size = 1 (0.8). I suspected it might be padding thing, but I was also able to reproduce this with same length sequences. I’m trying my luck here if anyone has encountered something similar and what the problem was?