Benchmark-Dual / instruments_pretrain.sh
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export WANDB_MODE=disabled
export CUDA_LAUNCH_BLOCKING=0
DATASET=Instruments
BASE_MODEL=$datain/v-yinju/llama-7b
ITEM_MODEL=$datain/v-yinju/rqvae-zzx/models/instruments/Apr-01-2024_01-25-11/best_collision_model.pth
USER_MODEL=$datain/v-yinju/rqvae-zzx/models/instruments/user/Apr-23-2024_03-36-04/best_collision_model.pth
DATA_PATH=$datain/v-yinju/rqvae-zzx/data
OUTPUT_DIR=$datain/v-yinju/rq-llama/v11.2/Ins
torchrun --nproc_per_node=8 pre-train.py \
--base_model $BASE_MODEL \
--item_model $ITEM_MODEL \
--user_model $USER_MODEL \
--output_dir $OUTPUT_DIR \
--dataset $DATASET \
--data_path $DATA_PATH \
--per_device_batch_size 6 \
--gradient_accumulation_steps 2 \
--learning_rate 5e-4 \
--epochs 4 \
--weight_decay 0.01 \
--save_and_eval_strategy epoch \
--deepspeed ./config/ds_z2_fp16.json \
--dataloader_num_workers 4 \
--only_train_response \
--tasks seqrec,itemsearch,inters2title,inters2description,preferenceobtain,item2index,index2item,intertitles2item,query2item,usersearch,user2pref,pref2user \
--train_prompt_sample_num 1,1,1,1,1,1,1,1,1,1,1,1 \
--train_data_sample_num 0,0,0,0,0,0,0,0,0,0,0,0 \
--index_file .index.json \
--user_index_file .user-index.json \
--fp16
cd convert
nohup ./convert.sh $OUTPUT_DIR >convert.log 2>&1 &
cd ..
CKPT_PATH=$datain/v-yinju/rq-llama/v11.2/Ins
python generate_embeddings.py \
--ckpt_path $CKPT_PATH \
--item_save_path $CKPT_PATH/embeddings.item.tsv \
--user_save_path $CKPT_PATH/embeddings.user.tsv \
--device_map 0
python generate_indices.py \
--ckpt_path $CKPT_PATH \
--item_data_path $CKPT_PATH/embeddings.item.tsv \
--user_data_path $CKPT_PATH/embeddings.user.tsv \
--save_path $CKPT_PATH \
--device_map 0
# DATASET=Games
# BASE_MODEL=/datain/v-yinju/llama-7b
# ITEM_MODEL=/datain/v-yinju/rqvae-zzx/models/games/Apr-18-2024_01-51-46/best_collision_model.pth
# USER_MODEL=/datain/v-yinju/rqvae-zzx/models/games/user/Jun-17-2024_18-40-36/best_collision_model.pth
# DATA_PATH=/datain/v-yinju/rqvae-zzx/data
# OUTPUT_DIR=/datain/v-yinju/rq-llama/v11/Games
# torchrun --nproc_per_node=8 pre-train.py \
# --base_model $BASE_MODEL \
# --item_model $ITEM_MODEL \
# --user_model $USER_MODEL \
# --output_dir $OUTPUT_DIR \
# --dataset $DATASET \
# --data_path $DATA_PATH \
# --per_device_batch_size 6 \
# --gradient_accumulation_steps 2 \
# --learning_rate 5e-5 \
# --epochs 4 \
# --weight_decay 0.01 \
# --save_and_eval_strategy epoch \
# --deepspeed ./config/ds_z2_fp16.json \
# --dataloader_num_workers 4 \
# --only_train_response \
# --tasks seqrec,itemsearch,inters2title,inters2description,preferenceobtain,item2index,index2item,intertitles2item,query2item,usersearch,user2pref,pref2user \
# --train_prompt_sample_num 1,1,1,1,1,1,1,1,1,1,1,1 \
# --train_data_sample_num 0,0,0,0,0,0,0,0,0,0,0,0 \
# --index_file .index.json \
# --user_index_file .user-index.json \
# --fp16
# cd convert
# nohup ./convert.sh $OUTPUT_DIR >convert.log 2>&1 &
# cd ..