Can we use a random state Bert model in BertGeneration?
I want to create anEncoderDecoderModelfor a translation task using aBert2Bertconfiguration, where the encoder model is pre-trained and frozen, and the decoder model is randomly initialized. In theBertGenerationdocument,  it says:We developed a Transformer-based sequence-to-sequence model that is compatible with publicly available pre-trained BERT, GPT-2 and RoBERTa checkpoints and conducted an extensive empirical study on the utility of initializing our model, both encoder and decoder, with these checkpoints.Can I use a new randomly initialized model in theBertGenerationDecoder? or it is better to useBertGenerationwith pre-trained models?model_config = BertConfig(
    vocab_size=tokenizer.vocab_size,
    hidden_size=hidden_size,
    add_cross_attention=True,
    is_decoder=True,
    bos_token_id=tokenizer.cls_token_id,
    eos_token_id=tokenizer.sep_token_id,
)
model = BertGenerationDecoder(config=model_config)