size mismatch for bert.embeddings.word_embeddings.weight

[LianghuiGuo]

Hello, I have trained a Bert with vocab_size 21128, and I noticed that in BLIP the vocab_size should be 21130 (including 2 additional tokens:DEC,ENC). However, this difference caused a shape conflict when loading statics from my Bert : "size mismatch for bert.embeddings.word_embeddings.weight: copying a param with shape torch.Size([21128, 768]) from checkpoint, the shape in current model is torch.Size([21130, 768])".

[futureisatyourhand]

Hello, I have trained a Bert with vocab_size 21128, and I noticed that in BLIP the vocab_size should be 21130 (including 2 additional tokens:DEC,ENC). However, this difference caused a shape conflict when loading statics from my Bert : "size mismatch for bert.embeddings.word_embeddings.weight: copying a param with shape torch.Size([21128, 768]) from checkpoint, the shape in current model is torch.Size([21130, 768])".

you can make sure your vocab size of med_config.json is more 2 than vocab_size of bert_config.json. I can train model.