-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathquery_score_train_best.sarray
41 lines (41 loc) · 4.21 KB
/
query_score_train_best.sarray
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
#!/bin/bash
#SBATCH --gres=gpu:1
#SBATCH --time=120:00:00
#SBATCH --array=0-9
#SBATCH --cpus-per-gpu=16
#SBATCH --mem=64G
#SBATCH --chdir=/neodudes
CUDA_DEVICE=$(echo "$CUDA_VISIBLE_DEVICES," | cut -d',' -f $((SLURM_LOCALID + 1)) );
T_REGEX='^[0-9]$';
if ! [[ "$CUDA_DEVICE" =~ $T_REGEX ]]; then
echo "error no reserved gpu provided"
exit 1;
fi
echo "Process $SLURM_PROCID of Job $SLURM_JOBID withe the local id $SLURM_LOCALID using gpu id +++$CUDA_DEVICE (we may use gpu: $CUDA_VISIBLE_DEVICES on $(hostname))"
echo "computing on $(nvidia-smi --query-gpu=gpu_name --format=csv -i $CUDA_DEVICE | tail -n 1)"
echo "stating job with ID $SLURM_ARRAY_TASK_ID"
export PYTHONPATH=/neodudes/src/
if [ $SLURM_ARRAY_TASK_ID -eq 0 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21" #
elif [ $SLURM_ARRAY_TASK_ID -eq 1 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 2 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 3 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 4 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 5 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 6 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 7 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 8 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 9 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
elif [ $SLURM_ARRAY_TASK_ID -eq 10 ]; then
python /neodudes/src/llm/query_score_training.py --model "google/flan-t5-small" --batchsize 64 --epochs 2 --ld "0.9013707813420198" --lr "1.3902932441715008e-05" --trials 1 --dataset "clampfp" --optunafile "gen_optuna_2024-06-21-best.log" --studyname "Query Score Best 2024-06-21"
fi
echo "done"