CCF BDCI BERT系统调优赛题baseline(Pytorch版本)

Overview

CCF BDCI BERT系统调优赛题baseline(Pytorch版本)

此版本基于Pytorch后端的huggingface进行实现。由于此实现使用了Oneflow的dataloader作为数据读入的方式,因此也需要安装Oneflow。其它框架的数据读取可以参考OneflowDataloaderToPytorchDataset类的实现。

使用说明

  1. 安装依赖(前置要求:已在环境中安装好PytorchOneflow

    pip install transformers pandas
    git clone https://github.com/tea321000/hugging_face_competition
    cd hugging_face_competition
  2. 运行train_BERT_base.sh和train_BERT_large.sh 单机单卡的baseline。保持其它参数不变,通过调节shell文件里的hidden_size参数,即可观察不同hidden_size所占显存的变化(可通过watch -n 0.1 nvidia-smi直观观察)

    python train.py \
    --ofrecord_path sample_seq_len_512_example \
    --lr 1e-4 --epochs 10 \
    --train_batch_size 2 \
    --seq_length=512 \
    --max_predictions_per_seq=80 \
    --num_hidden_layers=24 \
    --num_attention_heads=16 \
    --hidden_size=1024 \#要调节的参数
    --vocab_size=30522
Owner
Ziqi Zhou
Ziqi Zhou
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