Using TFOpenAIGPTLMHeadModel load pytorch model doesn't work well
I download file fromCDial-GPT_LCCC-large, and loaded as following way:tokenizer = BertTokenizer.from_pretrained(……,do_lower_case=True)
model_pt = OpenAIGPTLMHeadModel.from_pretrained(……)
model_tf = TFOpenAIGPTLMHeadModel.from_pretrained(……,from_pt=True)it’s fine when loadingOpenAIGPTLMHeadModel, but it encountered some problems as loadingTFOpenAIGPTLMHeadModel：Some weights of the PyTorch model were not used when initializing the TF 2.0 model TFOpenAIGPTLMHeadModel: ['transformer.h.2.attn.bias', 'transformer.h.5.attn.bias', 'transformer.h.9.attn.bias', 'transformer.h.6.attn.bias', 'transformer.h.0.attn.bias', 'lm_head.weight', 'transformer.h.8.attn.bias', 'transformer.h.3.attn.bias', 'transformer.h.1.attn.bias', 'transformer.h.10.attn.bias', 'transformer.h.4.attn.bias', 'transformer.h.11.attn.bias', 'transformer.h.7.attn.bias']
- This IS expected if you are initializing TFOpenAIGPTLMHeadModel from a PyTorch model trained on another task or with another architecture (e.g. initializing a TFBertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing TFOpenAIGPTLMHeadModel from a PyTorch model that you expect to be exactly identical (e.g. initializing a TFBertForSequenceClassification model from a BertForSequenceClassification model).
All the weights of TFOpenAIGPTLMHeadModel were initialized from the PyTorch model.
If your task is similar to the task the model of the checkpoint was trained on, you can already use TFOpenAIGPTLMHeadModel for predictions without further training.as i ignored this warning and went on, i got quite different logits, how can i solve this？