加载预训练模型出错

[DoubleSsh]

运行命令为python train.py --embedding --model_dir model_save_dir --dataset okvqa --validate 报错：Some weights of the model checkpoint at unc-nlp/lxmert-base-uncased were not used when initializing LxmertModel: ['obj_predict_head.decoder_dict.attr.weight', 'cls.predictions.decoder.weight', 'cls.predictions.bias', 'obj_predict_head.decoder_dict.obj.weight', 'obj_predict_head.decoder_dict.attr.bias', 'answer_head.logit_fc.2.weight', 'answer_head.logit_fc.3.weight', 'obj_predict_head.decoder_dict.obj.bias', 'answer_head.logit_fc.0.weight', 'obj_predict_head.transform.dense.weight', 'cls.predictions.transform.dense.weight', 'obj_predict_head.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'answer_head.logit_fc.3.bias', 'obj_predict_head.transform.dense.bias', 'cls.seq_relationship.weight', 'cls.seq_relationship.bias', 'answer_head.logit_fc.0.bias', 'obj_predict_head.decoder_dict.feat.bias', 'answer_head.logit_fc.2.bias', 'cls.predictions.transform.dense.bias', 'obj_predict_head.decoder_dict.feat.weight', 'obj_predict_head.transform.LayerNorm.weight', 'cls.predictions.transform.LayerNorm.bias']

• This IS expected if you are initializing LxmertModel 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 LxmertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). 9009 已杀死 请问这是什么原因呢？预训练模型（unc-nlp/lxmert-base-uncased）我是有下载的。在linux上运行的。

[tanshaosuannai]

大佬，我想请问一下这个unc-nlp/lxmert-base-uncased预训练模型在哪下载啊。

[tanshaosuannai]

运行命令为python train.py --embedding --model_dir model_save_dir --dataset okvqa --validate 报错：初始化 LxmertModel 时未使用 unc-nlp/lxmert-base-uncased 模型检查点的某些权重： ['obj_predict_head.decoder_dict.attr.weight'， 'cls.predictions.decoder.weight'， 'cls.predictions.bias'， 'obj_predict_head.decoder_dict.obj.weight'， 'obj_predict_head.decoder_dict.attr.bias'， 'answer_head.logit_fc.2.weight'， 'answer_head.logit_fc.3.weight'， 'obj_predict_head.decoder_dict.obj.bias'， 'answer_head.logit_fc.0.weight'， 'obj_predict_head.transform.dense.weight'， 'cls.predictions.transform.dense.weight'， 'obj_predict_head.transform.LayerNorm.bias'， 'cls.predictions.transform.LayerNorm.weight'， 'answer_head.logit_fc.3.bias'， 'obj_predict_head.transform.dense.bias'， 'cls.seq_relationship.weight'， 'cls.seq_relationship.bias'， 'answer_head.logit_fc.0.bias'， 'obj_predict_head.decoder_dict.feat.bias'， 'answer_head.logit_fc.2.bias'， 'cls.predictions.transform.dense.bias'， 'obj_predict_head.decoder_dict.feat.weight'， 'obj_predict_head.transform.LayerNorm.weight'， 'cls.predictions.transform.LayerNorm.bias']

• 如果要从在另一个任务上训练的模型的检查点初始化 LxmertModel，或者使用其他体系结构（例如，从 BertForPreTraining 模型初始化 BertForSequenceClassification 模型），则这是预期的。
• 如果从预期完全相同的模型的检查点初始化 LxmertModel（从 BertForSequenceClassification 模型初始化 BertForSequenceClassification 模型），则不需要这样做。 9009 已杀死 请问这是什么原因呢？预训练模型（unc-nlp/lxmert-base-uncased）我是有下载的。在linux上运行的。

大佬，我想请问一下这个unc-nlp/lxmert-base-uncased预训练模型在哪下载啊。

[xzr912]

运行命令为python train.py --embedding --model_dir model_save_dir --dataset okvqa --validate 报错：初始化 LxmertModel 时未使用 unc-nlp/lxmert-base-uncased 处的模型检查点的某些权重：['obj_predict_head.decoder_dict.attr.weight', 'cls.predictions.decoder.weight', 'cls.predictions.bias', 'obj_predict_head.decoder_dict.obj.weight', 'obj_predict_head.decoder_dict.attr.bias', 'answer_head.logit_fc.2.weight', 'answer_head.logit_fc.3.weight', 'obj_predict_head.decoder_dict.obj.bias', 'answer_head.logit_fc.0.weight', 'obj_predict_head.transform.dense.weight', 'cls.predictions.transform.dense.weight', 'obj_predict_head.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'answer_head.logit_fc.3.bias', 'obj_predict_head.transform.dense.bias', 'cls.seq_relationship.weight', 'cls.seq_relationship.bias', 'answer_head.logit_fc.0.bias', 'obj_predict_head.decoder_dict.feat.bias', 'answer_head.logit_fc.2.bias', 'cls.predictions.transform.dense.bias', 'obj_predict_head.decoder_dict.feat.weight', 'obj_predict_head.transform.LayerNorm.weight'，'cls.predictions.transform.LayerNorm.bias']

• 如果您正在从在另一个任务上或使用另一个架构训练的模型的检查点初始化 LxmertModel，则会出现这种情况（例如，从 BertForPreTraining 模型初始化 BertForSequenceClassification 模型）。
• 如果您从希望完全相同的模型的检查点初始化 LxmertModel（从 BertForSequenceClassification 模型初始化 BertForSequenceClassification 模型），则不会出现这种情况。 9009 已杀死 请问这是什么原因呢？预训练模型（unc-nlp/lxmert-base-uncased）我是有下载的。在linux上运行的。

我也遇到了这个问题，请问您知道了嘛？