#SBATCH --time=1:00:00 # walltime. hours:minutes:seconds | |
#SBATCH --ntasks=8 # number of processor cores (i.e. tasks) | |
#SBATCH --nodes=1 # number of nodes | |
#SBATCH --gpus=1 | |
#SBATCH --mem=80G # 164G memory per CPU core | |
#SBATCH --mail-user=aw742@byu.edu # email address | |
#SBATCH --mail-type=BEGIN | |
#SBATCH --mail-type=END | |
#SBATCH --mail-type=FAIL | |
#SBATCH --qos=cs | |
#SBATCH --partition=cs | |
# some helpful debugging options | |
set -e | |
set -u | |
# LOAD MODULES, INSERT CODE, AND RUN YOUR PROGRAMS HERE | |
# module load python/3.11 | |
source ./mse_env/Scripts/activate | |
# json config = "max_samples": 500, | |
# python mse_text_img_process.py | |
# python convert_mse.py | |
# pip install jsonlines | |
# pip install deepeval | |
NUM_TEST_CASES=100 | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --test f --shot 0 --out_file metric_test_orig_100_f.txt | |
# echo "Test case faithfulness finished" | |
NUM_SHOT=0 | |
# set DEEPEVAL_RESULTS_FOLDER=.\data | |
python mse_ollama_timer.py | |
echo "Test time calculated" | |
# deepeval set-local-model --model-name Hudson/llemma:7b | |
# ollama pull Hudson/llemma:7b | |
# deepeval set-ollama Hudson/llemma:7b | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_0_shot_100_ar" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test ar --shot $NUM_SHOT #--out_file metric_test_0_shot_100_ar.txt | |
# echo "Test case answer relevancy finished" | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_0_shot_100_crec" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test crec --shot $NUM_SHOT #--out_file metric_test_0_shot_100_crec.txt | |
# echo "Test case contexual recall finished" | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_0_shot_100_cp" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test cp --shot $NUM_SHOT #--out_file metric_test_0_shot_100_cp.txt | |
# echo "Test case contextual precision finished" | |
NUM_SHOT=1 | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_1_shot_100_ar" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test ar --shot $NUM_SHOT #--out_file metric_test_1_shot_100_ar.txt | |
# echo "Test case answer relevancy finished" | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_1_shot_100_crec" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test crec --shot $NUM_SHOT #--out_file metric_test_1_shot_100_crec.txt | |
# echo "Test case contexual recall finished" | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_1_shot_100_cp" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test cp --shot $NUM_SHOT #--out_file metric_test_1_shot_100_cp.txt | |
# echo "Test case contextual precision finished" | |
NUM_SHOT=5 | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_5_shot_100_ar" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test ar --shot $NUM_SHOT #--out_file metric_test_5_shot_100_ar.txt | |
# echo "Test case answer relevancy finished" | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_5_shot_100_crec" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test crec --shot $NUM_SHOT #--out_file metric_test_5_shot_100_crec.txt | |
# echo "Test case contexual recall finished" | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_5_shot_100_cp" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test cp --shot $NUM_SHOT #--out_file metric_test_5_shot_100_cp.txt | |
# echo "Test case contextual precision finished" | |
# python mse_ollama_run.py --num 25 --begin 0 --test cp --shot $NUM_SHOT --out_file metric_test_5_shot_25_cp.txt | |
# echo "Test case contextual precision finished" | |
# python mse_ollama_run.py --num 25 --begin 25 --test cp --shot $NUM_SHOT --out_file metric_test_5_shot_25_b25_cp.txt | |
# echo "Test case contextual precision finished (start 25)" | |
# python mse_ollama_run.py --num 25 --begin 50 --test cp --shot $NUM_SHOT --out_file metric_test_5_shot_25_b50_cp.txt | |
# echo "Test case contextual precision finished (start 50)" | |
# python mse_ollama_run.py --num 25 --begin 75 --test cp --shot $NUM_SHOT --out_file metric_test_5_shot_25_b75_cp.txt | |
# echo "Test case contextual precision finished (start 75)" | |
NUM_SHOT=10 | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_10_shot_100_ar" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test ar --shot $NUM_SHOT -out_file metric_test_10_shot_100_ar.txt | |
# echo "Test case answer relevancy finished" | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_10_shot_100_crec" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test crec --shot $NUM_SHOT -out_file metric_test_10_shot_100_crec.txt | |
# echo "Test case contexual recall finished" | |
# export DEEPEVAL_RESULTS_FOLDER="./metric_test_10_shot_100_cp" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test cp --shot $NUM_SHOT -out_file metric_test_10_shot_100_cp.txt | |
# echo "Test case contextual precision finished" | |
# finetuned | |
NUM_SHOT=0 | |
# export DEEPEVAL_RESULTS_FOLDER="metric_test_ft_100_ar" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test ar --shot $NUM_SHOT #> metric_test_ft_100_ar.txt | |
# echo "Test case answer relevancy finished" | |
# export DEEPEVAL_RESULTS_FOLDER="metric_test_ft_100_crec" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test crec --shot $NUM_SHOT #> metric_test_ft_100_crec.txt | |
# echo "Test case contexual recall finished" | |
# export DEEPEVAL_RESULTS_FOLDER="metric_test_ft_100_cp" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --begin 0 --test cp --shot $NUM_SHOT > metric_test_ft_100_cp.txt | |
# echo "Test case contextual precision finished" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --test crel --out_file metric_test_orig_100_crel.txt | |
# echo "Test case contextual relevancy finished" | |
# python mse_ollama_run.py --num $NUM_TEST_CASES --test f --out_file metric_test_orig_100_f.txt | |
# echo "Test case faithfulness finished" | |
# python mse_jsonl_resize.py | |
# python finetune.py | |
# echo "Original Llemma Model" | |
# echo "Processing 0 shot 100 test cases" | |
# CUDA_VISIBLE_DEVICES=0 python mse_deepeval_dataset.py --num 100 --shot 0 --dataset mse_llemma_orig_100_case_0_shot | |
# echo "Processing 1 shot 100 test cases" | |
# CUDA_VISIBLE_DEVICES=0 python mse_deepeval_dataset.py --num 100 --shot 1 --dataset mse_llemma_orig_100_case_1_shot | |
# echo "Processing 5 shot 100 test cases" | |
# CUDA_VISIBLE_DEVICES=0 python mse_deepeval_dataset.py --num 100 --shot 5 --dataset mse_llemma_orig_100_case_5_shot | |
# echo "Processing 10 shot 100 test cases" | |
# CUDA_VISIBLE_DEVICES=0 python mse_deepeval_dataset.py --num 100 --shot 10 --dataset mse_llemma_orig_100_case_10_shot |