Saving local bert/roberta model not working using save_pretrained
Hi,I am trying to tune BERT model and then save the pre-trained config file using model.save_pretrained but the config file didnt save.Due to security of my organization I cant directly download pre-trained bert model, so I download the models and files individually and then ran them locally.After training, I can save the tokenizer using tokenizer.save_pretrained and ‘.bin file’ using torch.save.But the mode.save_pretrained failed. I tried to check huggingface forums and  github issues but didnt find any solution.My tuned code:class BERT_Arch(torch.nn.Module):definit(self):super(BERT_Arch, self).init()config = BertConfig.from_pretrained(“/home/rp/projects/nlp/bert-base-uncased”, output_hidden_states=True)self.l1 = BertModel.from_pretrained(“/home/rp/projects/nlp/bert-base-cased”,config=config,ignore_mismatched_sizes=True)self.pre_dropout = torch.nn.Dropout(0.3)self.pre_classifier = torch.nn.Linear(768, 768)self.dropout = torch.nn.Dropout(0.3)self.classifier = torch.nn.Linear(768, 3)def forward(self, input_ids, attention_mask, token_type_ids):
    output_1 = self.l1(input_ids=input_ids, attention_mask=attention_mask, token_type_ids=token_type_ids)
    hidden_state = output_1[0]
    pooler = hidden_state[:, 0]
    pooler = self.dropout(pooler)
    pooler = self.pre_classifier(pooler)
    pooler = torch.nn.ReLU()(pooler)
    pooler = self.dropout(pooler)
    output = self.classifier(pooler)
    return outputmodel = BERT_Arch()model = model.to(device)####savingmodelsoutput_dir = ‘/home/rp/projects/nlp/dl_models/model2/’Create output directory if neededif not os.path.exists(output_dir):os.makedirs(output_dir)print(“Saving model to %s” % output_dir)Save a trained model, configuration and tokenizer usingsave_pretrained().tokenizer.save_pretrained(output_dir)model_to_save = model.module if hasattr(model, ‘module’) else model  # Take care of distributed/parallel trainingmodel_to_save.save_pretrained(output_dir)Can anyone point out any issue in my code?