add z-1 pred

pre_test.sh

-CUDA_VISIBLE_DEVICES=5 python run_interaction.py --task=test --b=64 --output=./predict/lr-1e-5-batch-32-e-10-layer9-0429-z-10-step-74133 --config=./config/config_layer_9.json --init=./model/lr-1e-5-batch-32-e-10-layer9-0429-z-10/epoch-8-step-74133-loss-24.790190863309736.pth --do_eval=False
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+CUDA_VISIBLE_DEVICES=1 python run_interaction.py --task=test --b=64 --output=./predict/lr-1e-5-batch-32-e-10-layer3-0503-z-1-step-65896 --config=./config/config_layer_3.json --init=./model/lr-1e-5-batch-32-e-10-layer3-0503-z-1/epoch-7-step-65896-loss-0.39236504916727866.pth --do_eval=False
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predict/lr-1e-5-batch-32-e-10-layer9-0429-z-10-step-74133/eval_results

-RMSE : 1.3901506777912391 ; Pearson Correlation Coefficient : 0.7332126683709385
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+RMSE : 1.3901506777912391 ; Pearson Correlation Coefficient : 0.7332126683709386
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run_interaction.py

@@ -159,7 +159,7 @@ def main(args):
     print('model name : BertAffinity')
     print('task name : {}'.format(args.task))
 
-    if args.task in ['train', 'train_z_10', 'train_z_100']:
+    if args.task in ['train', 'train_z_1', 'train_z_10', 'train_z_100']:
         train(args, model, dataset)
 
     elif args.task in ['test']:

train.sh

-CUDA_VISIBLE_DEVICES=2 python run_interaction.py --b=32 --task=train_z_10 --epochs=10 --lr=1e-5 --savedir=lr-1e-5-batch-32-e-10-layer9-0429-z-10 --config=./config/config_layer_9.json
+CUDA_VISIBLE_DEVICES=7 python run_interaction.py --b=32 --task=train_z_1 --epochs=20 --lr=1e-5 --savedir=lr-1e-5-batch-32-e-20-layer3-0503-z-1 --config=./config/config_layer_3.json