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bert_classfication's Introduction

qukequke

第一个不行,再来一个

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bert_classfication's Issues

更换训练数据后,类别数更改就报错,原来18类别现在2类别

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.

训练的时候会一直卡在GET_MODEL这一步上

    * 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

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