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run.sh
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#!/usr/bin/env bash
export OMP_NUM_THREADS=16
export CUDA_VISIBLE_DEVICES=0
for dataset in 'clinc' 'banking'
do
for seed in 42
do
for known_cls_ratio in 0.1 0.25
do
for labeled_ratio in 0.1
do
for query_samples in 500 # 1 50 100 300 500 1000 2000
do
for sampling_strategy in 'highest' # 'random' 'highest' 'loop'
do
for options in 5 # 5 10
do
for options_cluster_instance_ratio in 0.5 # 0.1 0.25, 0.5, 0.75 1
do
for weight_cluster_instance_cl in 0.1 0.05
do
for llm in "gpt-4o-mini-2024-07-18" # deepseek-ai/DeepSeek-V3
do
echo "Dataset: ${dataset}"
echo "Running with known_cls_ratio=${known_cls_ratio}, labeled_ratio=${labeled_ratio}, query_samples=${query_samples}"
echo "Running with sampling_strategy=${sampling_strategy}, weight_cluster_instance_cl=${weight_cluster_instance_cl}"
echo "Running with options=${options}, options_cluster_instance_ratio=${options_cluster_instance_ratio}"
echo "Running with llm=${llm}"
python GCDLLMs.py \
--data_dir data \
--dataset $dataset \
--known_cls_ratio $known_cls_ratio \
--labeled_ratio $labeled_ratio \
--seed $seed \
--num_train_epochs 25 \
--lr '1e-5' \
--save_results_path 'outputs' \
--view_strategy 'rtr' \
--save_premodel \
--experiment_name 'GCDLLMs_gpt4omini' \
--running_method 'GCDLLMs' \
--architecture 'Loop' \
--update_per_epoch 5 \
--ce_weight 1 \
--cl_weight 1 \
--sup_weight 1 \
--weight_cluster_instance_cl $weight_cluster_instance_cl \
--weight_ce_unsup 0 \
--query_samples $query_samples \
--options $options \
--train_batch_size 48 \
--pretrain_batch_size 48 \
--sampling_strategy $sampling_strategy \
--options_cluster_instance_ratio $options_cluster_instance_ratio \
--llm $llm \
--api_key 'YOUR_API_KEY'
done
done
done
done
done
done
done
done
done
done