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达观算法比赛ner任务,从重新训练bert,到finetune预测。
请问: bert_lstm_crf.py中为啥计算loss的时候还要除以 batch_size,因为构造函数的时候CRF(target_size=tagset_size, average_batch=True, use_cuda=use_cuda)
已经设置 average_batch为True了??
loss_value = self.crf.neg_log_likelihood_loss(lstm_feats, mask, tags)
batch_size = lstm_feats.size(0)
loss_value /= float(batch_size)
你好,我尝试训练bert,1080ti*4。不管怎么设置,都只用了第一块gpu,另外三块的显存占用基本只有100M。我调大batchsize=64后就会OOM,请问您有这种情况吗?和代码里面用的TPU优化器有关吗?谢谢!
非常感谢楼主开源代码!我换了自己的数据集跑代码的时候出现这个警告,尝试解决了很多方案仍没有解决,来求助您是否见过这个警告?寻求解决方案感谢🙏
Warning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (masked_fill__cuda at /opt/conda/conda-bld/pytorch_1579022060824/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:19)
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