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run_selfrag_no_threshold.sh
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run_selfrag_no_threshold.sh
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retrieval_mode="adaptive_retrieval"
temperature=0.0
top_p=1.0
max_tokens=100
doc_top_n=5
seed=20
limit_input=0
model_name="selfrag/selfrag_llama2_7b"
metric="match"
input_data_path="./data/retrievalqa.jsonl"
declare -a data=("retrievalqa")
for data_source in "${data[@]}"
do
echo "================ Running: $data_source | Retrieval mode: $retrieval_mode | Seed: $seed ================"
output_prediction_path="./results/${retrieval_mode}/${model_name}/threshold_none/predict_${data_source}_seed$seed.jsonl"
output_score_path="./results/${retrieval_mode}/${model_name}/threshold_none/score_${data_source}_seed$seed.json"
echo $output_prediction_path
echo $output_score_path
python ./run_selfrag_no_threshold.py \
--model_name $model_name \
--data_source $data_source \
--retrieval_mode $retrieval_mode \
--input_data_path $input_data_path \
--output_score_path $output_score_path \
--output_prediction_path $output_prediction_path \
--temperature $temperature \
--top_p $top_p \
--max_tokens $max_tokens \
--doc_top_n $doc_top_n \
--limit_input $limit_input \
--metric $metric \
--seed $seed
echo ""
done