qukequke / bert_classfication Goto Github PK

RuntimeError: Error(s) in loading state_dict for RobertaForSequenceClassification:
size mismatch for classifier.out_proj.weight: copying a param with shape torch.Size([18, 768]) from checkpoint, the shape in current model is torch.Size([2, 768]).
size mismatch for classifier.out_proj.bias: copying a param with shape torch.Size([18]) from checkpoint, the shape in current model is torch.Size([2]).
You may consider adding ignore_mismatched_sizes=True in the model from_pretrained method.

因为中文的分类数据集太少了，找了半天也没找到怎么修改从网上下载模型参数/模型的链接，想试试跑英文分类！如果方便的话作者能提供一下VX嘛？再次感谢作者

是数据title的问题吗

    * Building model...

Some weights of the model checkpoint at nghuyong/ernie-1.0 were not used when initializing BertForSequenceClassification: ['cls.predictions.decoder.bias', 'cls.predictions.transform.dense.bias', 'cls.predictions.decoder.weight', 'cls.predictions.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight']

• This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
• This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
  Some weights of BertForSequenceClassification were not initialized from the model checkpoint at nghuyong/ernie-1.0 and are newly initialized: ['classifier.bias', 'classifier.weight']
  You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

输出这些之后就一直卡住