This is a fork of the PyTorch-Transformers repo for the FEVER symmetric dataset processor and weighted loss. For more details, see the FeverSymmetric repository.
python examples/run_glue.py \
--task_name fever \
--do_train \
--do_eval \
--do_lower_case \
--model_type bert \
--data_dir PATH_TO_DATA_DIR \
--model_name_or_path bert-base-uncased \
--max_seq_length 128 \
--per_gpu_train_batch_size 32 \
--learning_rate 2e-5 \
--num_train_epochs 3.0 \
--save_steps 100000 \
--output_dir output/baseline
to use the per sample weights, use the --weighted_loss
flag.
python examples/run_glue.py \
--task_name fever \
--do_eval \
--output_preds \
--do_lower_case \
--model_type bert \
--data_dir PATH_TO_DATA_DIR \
--model_name_or_path bert-base-uncased \
--max_seq_length 128 \
--output_dir output/baseline