train(){ python run_classifier.py \ --data_dir data/STS-B \ --verbose True \ --shuffle false \ --init_checkpoint xlnet_cased_L-12_H-768_A-12/params \ --predict_dir exp/sts-b \ --model_config_path xlnet_cased_L-12_H-768_A-12/xlnet_config.json \ --uncased False \ --save_steps 50 \ --train_steps 50 \ --epoch 1 \ --skip_steps 10 \ --validation_steps 30 \ --task_name sts-b \ --warmup_steps 5 \ --random_seed 100 \ --spiece_model_file xlnet_cased_L-12_H-768_A-12/spiece.model \ --checkpoints checkpoints_sts-b \ --is_regression True \ --use_cuda True \ --eval_batch_size 4 \ --enable_ce } export CUDA_VISIBLE_DEVICES=0 train | python _ce.py export CUDA_VISIBLE_DEVICES=0,1,2,3 train | python _ce.py
