Reproduction process of BERT on SST2 dataset

Overview

BERT-SST2-Prod

Reproduction process of BERT on SST2 dataset

安装说明

  • 下载代码库
git clone https://github.com/JunnYu/BERT-SST2-Prod
  • 进入文件夹,安装requirements
pip install -r requirements.txt
  • 安装PaddlePaddle与PyTorch
# CPU版本的PaddlePaddle
pip install paddlepaddle==2.2.0 -i https://mirror.baidu.com/pypi/simple
# 如果希望安装GPU版本的PaddlePaddle,可以使用下面的命令
# pip install paddlepaddle-gpu==2.2.0.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
# 安装PyTorch
pip install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html

注意: 本项目依赖于paddlepaddle-2.2.0版本,安装时需要注意。

  • 验证PaddlePaddle是否安装成功

运行python,输入下面的命令。

import paddle
paddle.utils.run_check()
print(paddle.__version__)

如果输出下面的内容,则说明PaddlePaddle安装成功。

PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now.
2.2.0
  • 验证PyTorch是否安装成功

运行python,输入下面的命令,如果可以正常输出,则说明torch安装成功。

import torch
print(torch.__version__)
# 如果安装的是cpu版本,可以按照下面的命令确认torch是否安装成功
# 期望输出为 tensor([1.])
print(torch.Tensor([1.0]))
# 如果安装的是gpu版本,可以按照下面的命令确认torch是否安装成功
# 期望输出为 tensor([1.], device='cuda:0')
print(torch.Tensor([1.0]).cuda())
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