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ML
ffm-baseline
Commits
79dd5fab
Commit
79dd5fab
authored
Dec 20, 2018
by
王志伟
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Merge branch 'master' of
http://git.wanmeizhensuo.com/ML/ffm-baseline
parents
661fd3fe
ad60dfa8
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submit.sh
eda/esmm/Model_pipline/submit.sh
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eda/esmm/Model_pipline/submit.sh
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79dd5fab
...
...
@@ -14,6 +14,7 @@ rm ${DATA_PATH}/tr/*
rm
${
DATA_PATH
}
/va/
*
rm
${
DATA_PATH
}
/native/
*
rm
${
DATA_PATH
}
/nearby/
*
rm
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/2018
*
echo
"data2ffm"
${
PYTHON_PATH
}
${
MODEL_PATH
}
/Feature_pipline/data2ffm.py
>
${
DATA_PATH
}
/infer.log
...
...
@@ -47,7 +48,7 @@ currentTimeStamp=$((timeStamp*1000+`date "+%N"`/1000000))
echo
$current
echo
"train..."
${
PYTHON_PATH
}
${
MODEL_PATH
}
/Model_pipline/DeepCvrMTL.py
--ctr_task_wgt
=
0.3
--learning_rate
=
0.0001
--deep_layers
=
256,128
--dropout
=
0.8,0.5
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
23
--feature_size
=
354332
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
--task_type
=
train
${
PYTHON_PATH
}
${
MODEL_PATH
}
/Model_pipline/DeepCvrMTL.py
--ctr_task_wgt
=
0.3
--learning_rate
=
0.0001
--deep_layers
=
256,128
--dropout
=
0.8,0.5
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
8
--feature_size
=
354332
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
--task_type
=
train
echo
"train time"
current
=
$(
date
"+%Y-%m-%d %H:%M:%S"
)
...
...
@@ -56,11 +57,11 @@ currentTimeStamp=$((timeStamp*1000+`date "+%N"`/1000000))
echo
$current
echo
"infer native..."
${
PYTHON_PATH
}
${
MODEL_PATH
}
/Model_pipline/DeepCvrMTL.py
--ctr_task_wgt
=
0.3
--learning_rate
=
0.0001
--deep_layers
=
256,128
--dropout
=
0.8,0.5
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
23
--feature_size
=
354332
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
/native
--task_type
=
infer
>
${
DATA_PATH
}
/infer.log
${
PYTHON_PATH
}
${
MODEL_PATH
}
/Model_pipline/DeepCvrMTL.py
--ctr_task_wgt
=
0.3
--learning_rate
=
0.0001
--deep_layers
=
256,128
--dropout
=
0.8,0.5
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
8
--feature_size
=
354332
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
/native
--task_type
=
infer
>
${
DATA_PATH
}
/infer.log
echo
"infer nearby..."
${
PYTHON_PATH
}
${
MODEL_PATH
}
/Model_pipline/DeepCvrMTL.py
--ctr_task_wgt
=
0.3
--learning_rate
=
0.0001
--deep_layers
=
256,128
--dropout
=
0.8,0.5
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
23
--feature_size
=
354332
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
/nearby
--task_type
=
infer
>
${
DATA_PATH
}
/infer.log
${
PYTHON_PATH
}
${
MODEL_PATH
}
/Model_pipline/DeepCvrMTL.py
--ctr_task_wgt
=
0.3
--learning_rate
=
0.0001
--deep_layers
=
256,128
--dropout
=
0.8,0.5
--optimizer
=
Adam
--num_epochs
=
1
--embedding_size
=
16
--batch_size
=
1024
--field_size
=
8
--feature_size
=
354332
--l2_reg
=
0.005
--log_steps
=
100
--num_threads
=
36
--model_dir
=
${
DATA_PATH
}
/model_ckpt/DeepCvrMTL/
--data_dir
=
${
DATA_PATH
}
/nearby
--task_type
=
infer
>
${
DATA_PATH
}
/infer.log
echo
"sort and 2sql"
${
PYTHON_PATH
}
${
MODEL_PATH
}
/Model_pipline/sort_and_2sql.py
...
...
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