the train result is very bad, test_auc is 0.526, train as the procedure, what's wrong?

[PhenixY]

train according to the procedure：
mkdir Criteo
python ./Dataprocess/Criteo/preprocess.py
python ./Dataprocess/Kfold_split/stratifiedKfold.py
python ./Dataprocess/Criteo/scale.py
Here's how to run the training.

      python -u train.py \
                             --data "Criteo"  --blocks 3 --heads 2  --block_shape "[64, 64, 64]" \
                             --is_save "True" --save_path "./test_code/Criteo/b3h2_64x64x64/"  \
                             --field_size 39  --run_times 1 --data_path "./" \
                             --epoch 3 --has_residual "True"  --has_wide "False" \
                             --batch_size 1024 \
                             > test_code_single.out &

but the result is not same with the example:
train logs
...
start testing!...
restored from ./test_code/Criteo/b3h2_dnn_dropkeep1_400x2/1/
test-result = 0.8088, test-logloss = 0.4430
test_auc [0.8088305055534442]
test_log_loss [0.44297631300399626]
avg_auc 0.8088305055534442
avg_log_loss 0.44297631300399626

my result is :
start testing!...
restored from ./test_code/Criteo/b3h2_64x64x64/1/
test-result = 0.5263, test-logloss = 0.5751
test_auc [0.5262644664774784]
test_log_loss [0.5751133874248523]
avg_auc 0.5262644664774784
avg_log_loss 0.5751133874248523