#!/bin/bash

DATA=svhn
MODE=nblora

RANK=16
LR=5e-3
EPOCH=10
STEP=4000

CUDA_VISIBLE_DEVICES=0 python train.py \
    --dataset $DATA \
    --ft_mode $MODE \
    --lora_r $RANK \
    --lora_gamma 1.6 \
    --lora_sp nuc \
    --log_steps $STEP \
    --epochs $EPOCH \
    --lr $LR 

# for RANK in 16 32 64; do

#    CUDA_VISIBLE_DEVICES=0 python train.py \
#       --dataset $DATA \
#       --ft_mode $MODE \
#       --lora_r $RANK \
#       --lora_gamma 0.1 \
#       --lora_sp nuc \
#       --log_steps 20

# done
  
# RANK=16
# for LR in 0.002 0.01 0.02; do

#    CUDA_VISIBLE_DEVICES=0 python train.py \
#       --dataset $DATA \
#       --ft_mode $MODE \
#       --lora_r $RANK \
#       --lora_gamma 0.1 \
#       --lora_sp nuc \
#       --lr $LR \
#       --log_steps 20

# done

# RANK=16
# for EP in 2 3 4; do 

#    EPOCH=$((10*EP))
#    STEP=$((20*EP))
#    CUDA_VISIBLE_DEVICES=0 python train.py \
#       --dataset $DATA \
#       --ft_mode $MODE \
#       --lora_r $RANK \
#       --lora_gamma 0.1 \
#       --lora_sp nuc \
#       --epoch $EPOCH \
#       --log_steps $STEP

# done 
