For PyTorch practice and graduation
You don't need to download dataset or models by hand.
You just simply use awesome packages such as datasets, transformers, etc.
pip install -r requirements.txt
(ml) udnet@dmcb-System:~/graduation/pytorch_nlp$ python sst2_bert.py -h
usage: sst2_bert.py [-h] [--gpu_num GPU_NUM] [--num_train_data NUM_TRAIN_DATA] [--num_seed NUM_SEED] [--num_epochs NUM_EPOCHS] [--backt] [--eda] [--masked_lm]
Set some arguments for training
options:
-h, --help show this help message and exit
--gpu_num GPU_NUM gpu num you want to use
--num_train_data NUM_TRAIN_DATA
the number of the training data
--num_seed NUM_SEED the number of the seeds
--num_epochs NUM_EPOCHS
the number of the epochs
--backt augment training data by backtranslation
--eda augment training data by EDA
--masked_lm augment training data by masked language model
If you want to see the result after training with augmented data by EDA with gpu 1
python sst2_bert.py --gpu_num 1 --eda
If you want to see the result after training with augmented data by backtranslation with gpu 2, with 30 seeds, with 200 epochs
python sst2_bert.py --gpu_num 2 --backt --num_seed 30 --num_epochs 200