Comments (5)
from bert-gpu.
After removing the --do_eval=True , there is still no output
masked_lm_accuracy
"masked_lm_loss":
"next_sentence_accuracy":
"next_sentence_loss":
from bert-gpu.
set --do_eval=False
from bert-gpu.
from bert-gpu.
Loss is enough for judging that pretraining is working.
from bert-gpu.
Related Issues (20)
- run_pretraining_gpu.py not working HOT 5
- wrong when run_pretraining_gpu_v2 with init_checkpoint HOT 3
- Output model files compatible with Official Bert's pre-trained models? HOT 9
- OOM error HOT 1
- Suffer the Error: tensorflow.python.framework.errors_impl.InvalidArgumentError HOT 8
- Question about "init_checkpoint" and "output_dir" checkpint HOT 9
- XLNet support HOT 3
- GPT support
- The `global_step` update in `optimization_gpu.py` (line 74-75) is redundant. HOT 2
- TensorFlow2 support
- num_train_steps是一块卡还是多块卡的step? HOT 4
- 《How To Pre-train BERT In GPUs》
- 【Try】1-GPU pretrain with big learning rate for 100W-step, then 1-GPU pretrain with small learning rate for another 100W-step.
- train_batch_size and time required to pretrain HOT 2
- 关于多GPU训练的一些疑问咨询? HOT 13
- train 10W steps结束后,do_eva阶段出现错误 HOT 3
- Should line 74-75 in optimization_gpu.py be comment out? HOT 1
- an error like this : Segmentation fault (core dumped),Is the configuration wrong? HOT 9
- 请问如何进一步实现梯度累计的功能? HOT 1
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from bert-gpu.