liqi / code /pmps /train_direct_match.sh
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#!/bin/bash
# Ablation: Direct Soft Matching (no prototypes)
# Uses train_direct_match.py instead of train.py
rm -rf ms-swift/ms_swift.egg-info
CLUSTER_CONFIG='./cluster.json'
cat <<EOT > ${CLUSTER_CONFIG}
{
"worker": {
"gpu": 100,
"cpu": 1200,
"memory": 50000
}
}
EOT
WORKER_COUNT=8
args="--config_file=./args/gsm_codi_direct_match_train.yaml"
nebulactl run mdl --engine=xdl \
--refresh \
--ignore=data/*,tools/pycocoevalcap/*,tools/pycocotools/*,.git/*,analysis/results/*,plot/* \
--queue=pailitao_algo_high_2 \
--worker_count=$WORKER_COUNT \
--odps_project=pailitao_algo_high_2 \
--entry="./train_direct_match.py" \
--oss_access_id=LTAI5tMZb5HHH6HHgAExAyiL \
--oss_access_key=6MVP8JnTE01t4TLUHhPoFV0swZNTrb \
--oss_bucket=pailitao-ai \
--oss_endpoint=ossproxy.alibaba-inc.com \
--algo_name=pytorch260 \
--user_params="$args" \
--job_name=gpt2-gsm8k_ablation_direct_match_mt0.1_fac0.5_l6_lr3e3_btz256_pos2_ep30-train \
--file.cluster_file=$CLUSTER_CONFIG \
--force \
--max_failover_times=2 \
--requirements_file_name="./requirements.txt"
rm ${CLUSTER_CONFIG}