# python xgb_tabpfn.py --seed 0 --data_id 31 #credit-g
# python xgb_tabpfn.py --seed 0 --data_id 54 #vehicle
# python xgb_tabpfn.py --seed 0 --data_id 973 #wine
# python xgb_tabpfn.py --seed 0 --data_id 1464 #blood-transfusion
# python xgb_tabpfn.py --seed 0 --data_id 40981 #Australian
# python xgb_tabpfn.py --seed 0 --data_id  1461 #bank-marketing
# python xgb_tabpfn.py --seed 0 --data_id 1590 #adult
# python xgb_tabpfn.py --seed 0 --data_id 41027 #jungle_chess_2pcs
# # python xgb_tabpfn.py --seed 0 --data_id 1169 #airlines
# python xgb_tabpfn.py --seed 0 --data_id 40975 #car
# python xgb_tabpfn.py --seed 0 --data_id 31 #credit-g
# python xgb_tabpfn.py --seed 0 --data_id 54 #vehicle
# python xgb_tabpfn.py --seed 0 --data_id 973 #wine
# python xgb_tabpfn.py --seed 0 --data_id 1464 #blood-transfusion
# python xgb_tabpfn.py --seed 0 --data_id 40981 #Australian
# python xgb_tabpfn.py --seed 0 --data_id  1461 #bank-marketing
# python xgb_tabpfn.py --seed 0 --data_id 1590 #adult
# python xgb_tabpfn.py --seed 0 --data_id 41027 #jungle_chess_2pcs
# # python xgb_tabpfn.py --seed 0 --data_id 1169 #airlines
# python xgb_tabpfn.py --seed 0 --data_id 40975 #car
# python xgb_tabpfn.py --seed 0 --data_id 31 #credit-g
# python xgb_tabpfn.py --seed 0 --data_id 54 #vehicle
# python xgb_tabpfn.py --seed 0 --data_id 973 #wine
# python xgb_tabpfn.py --seed 0 --data_id 1464 #blood-transfusion
# python xgb_tabpfn.py --seed 0 --data_id 40981 #Australian
# python xgb_tabpfn.py --seed 0 --data_id  1461 #bank-marketing
# python xgb_tabpfn.py --seed 0 --data_id 1590 #adult
# python xgb_tabpfn.py --seed 0 --data_id 41027 #jungle_chess_2pcs
# # python xgb_tabpfn.py --seed 0 --data_id 1169 #airlines
# python xgb_tabpfn.py --seed 0 --data_id 40975 #car
# python xgb_tabpfn.py --seed 0 --data_id 31 #credit-g
# python xgb_tabpfn.py --seed 0 --data_id 54 #vehicle
# python xgb_tabpfn.py --seed 0 --data_id 973 #wine
# python xgb_tabpfn.py --seed 0 --data_id 1464 #blood-transfusion
# python xgb_tabpfn.py --seed 0 --data_id 40981 #Australian
# python xgb_tabpfn.py --seed 0 --data_id  1461 #bank-marketing
# python xgb_tabpfn.py --seed 0 --data_id 1590 #adult
# python xgb_tabpfn.py --seed 0 --data_id 41027 #jungle_chess_2pcs
# # python xgb_tabpfn.py --seed 0 --data_id 1169 #airlines
# python xgb_tabpfn.py --seed 0 --data_id 40975 #car
# python xgb_tabpfn.py --seed 0 --data_id 31 #credit-g
# python xgb_tabpfn.py --seed 0 --data_id 54 #vehicle
# python xgb_tabpfn.py --seed 0 --data_id 973 #wine
# python xgb_tabpfn.py --seed 0 --data_id 1464 #blood-transfusion
# python xgb_tabpfn.py --seed 0 --data_id 40981 #Australian
# python xgb_tabpfn.py --seed 0 --data_id  1461 #bank-marketing
# python xgb_tabpfn.py --seed 0 --data_id 1590 #adult
# python xgb_tabpfn.py --seed 0 --data_id 41027 #jungle_chess_2pcs
# # python xgb_tabpfn.py --seed 0 --data_id 1169 #airlines
# python xgb_tabpfn.py --seed 0 --data_id 40975 #car


python xgb_tabpfn.py --seed 0 --data_path ./data/Adult/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Adult/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Adult/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Adult/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Adult/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Adult/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/Adult/prototypes-naturallanguage-performance-0 --cv_folds 5 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_shuffled_zero_flan --train_size 20 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_shuffled_zero_flan --train_size 50 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_shuffled_zero_flan --train_size 100 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_shuffled_zero_flan --train_size 200 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_shuffled_zero_flan --train_size 500 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_shuffled_zero_flan --train_size 1000 --cv_folds 20
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_shuffled_zero_flan --cv_folds 5 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_direct_zero_flan --train_size 20 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_direct_zero_flan --train_size 50 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_direct_zero_flan --train_size 100 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_direct_zero_flan --train_size 200 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_direct_zero_flan --train_size 500 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_direct_zero_flan --train_size 1000 --cv_folds 20
# python xgb_tabpfn.py --seed 0 --data_path ./data/adult_direct_zero_flan --cv_folds 5 --val_size 0.2

python xgb_tabpfn.py --seed 0 --data_path ./data/Abalone/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Abalone/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Abalone/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Abalone/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Abalone/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Abalone/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/Abalone/prototypes-naturallanguage-performance-0 --cv_folds 10 --val_size 0.2 

python xgb_tabpfn.py --seed 0 --data_path ./data/BreastCancer/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/BreastCancer/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/BreastCancer/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/BreastCancer/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/BreastCancer/prototypes-naturallanguage-performance-0 --cv_folds 40 --val_size 0.2

python xgb_tabpfn.py --seed 0 --data_path ./data/Churn/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Churn/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Churn/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Churn/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Churn/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Churn/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/Churn/prototypes-naturallanguage-performance-0 --cv_folds 10 --val_size 0.2

python xgb_tabpfn.py --seed 0 --data_path ./data/HeartDisease/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/HeartDisease/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/HeartDisease/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/HeartDisease/prototypes-naturallanguage-performance-0 --cv_folds 40 --val_size 0.2

python xgb_tabpfn.py --seed 0 --data_path ./data/Sharktank/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Sharktank/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Sharktank/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Sharktank/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Sharktank/prototypes-naturallanguage-performance-0 --cv_folds 40 --val_size 0.2

python xgb_tabpfn.py --seed 0 --data_path ./data/Statlog/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Statlog/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Statlog/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/Statlog/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Statlog/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Statlog/prototypes-naturallanguage-performance-0 --cv_folds 20 --val_size 0.2

python xgb_tabpfn.py --seed 0 --data_path ./data/UEFA/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/UEFA/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/UEFA/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/UEFA/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/UEFA/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/UEFA/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/UEFA/prototypes-naturallanguage-performance-0 --cv_folds 10 --val_size 0.2

python xgb_tabpfn.py --seed 0 --data_path ./data/Wine/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Wine/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Wine/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/Wine/prototypes-naturallanguage-performance-0 --cv_folds 40 --val_size 0.2

python xgb_tabpfn.py --seed 0 --data_path ./data/SoybeanLarge/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/SoybeanLarge/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/SoybeanLarge/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/SoybeanLarge/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 40 
python xgb_tabpfn.py --seed 0 --data_path ./data/SoybeanLarge/prototypes-naturallanguage-performance-0 --cv_folds 40 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/bank/prototypes-naturallanguage-performance-0 --cv_folds 5 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/calhousing/prototypes-naturallanguage-performance-0 --cv_folds 5 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/income/prototypes-naturallanguage-performance-0 --cv_folds 5 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/jungle/prototypes-naturallanguage-performance-0 --cv_folds 5 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/blood/prototypes-naturallanguage-performance-0 --cv_folds 10 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/car/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/car/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/car/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/car/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/car/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/car/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/car/prototypes-naturallanguage-performance-0 --cv_folds 10 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/creditg/prototypes-naturallanguage-performance-0 --cv_folds 10 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/diabetes/prototypes-naturallanguage-performance-0 --cv_folds 10 --val_size 0.2

# python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --train_size 8 --cv_folds 40
# python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --train_size 16 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --train_size 20 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --train_size 50 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --train_size 100 --cv_folds 40
python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --train_size 200 --cv_folds 20
python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --train_size 500 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --train_size 1000 --cv_folds 10
python xgb_tabpfn.py --seed 0 --data_path ./data/heart/prototypes-naturallanguage-performance-0 --cv_folds 10 --val_size 0.2