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For questions related to BERT (which stands for Bidirectional Encoder Representations from Transformers), a language representation model introduced in the paper "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" (2019) by Google.

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BERT: After pretraining 880000 step, why fine-tune not work? [closed]

training step 895429, loss 4.95, acc 0.082 dev loss 4.843, acc 0.092 Without restore the pretrained ckpt: epoch 1: training step 10429, loss 2.48, acc 0.606 dev loss 1.604, acc 0.8036 Restore the google's BERT-Base … Or restore from a pretrained ckpt pretrained from https://github.com/guotong1988/BERT-GPU epoch 1: training loss 1.89, acc 0.761 dev loss 1.351, acc 0.869 …
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BERT: After pretraining 880000 step, why fine-tune not work?

change bert_output = bert_model.get_pooled_output() to bert_output = tf.reduce_mean(bert_model.get_sequence_output()[:,1:,:],1)
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