其中损失函数采用了sigmoid+BCE
苏神提出的——multilabel_crossentropy
python train_bert_mutillabel_classification.py
BCE train_acc:1.0000 val_acc:0.9720------best_acc:0.9720
MLCE train_acc:1.0000 val_acc:0.9790------best_acc:0.9790
其中损失函数采用了sigmoid+BCE
苏神提出的——multilabel_crossentropy
python train_bert_mutillabel_classification.py
BCE train_acc:1.0000 val_acc:0.9720------best_acc:0.9720
MLCE train_acc:1.0000 val_acc:0.9790------best_acc:0.9790
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