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TASKS=("cola" "sst2" "mrpc" "qqp" "mnli" "qnli" "rte" "wnli")
# Create a directory for logs in the current working directory
LOG_DIR="./baseline"
mkdir -p "$LOG_DIR"
# Loop through each task
for TASK_NAME in "${TASKS[@]}"; do
# Set epochs to 5 for MRPC and WNLI, otherwise 3
if [[ "$TASK_NAME" == "mrpc" || "$TASK_NAME" == "wnli" ]]; then
NUM_EPOCHS=5
else
NUM_EPOCHS=3
fi
echo "Running training for task: $TASK_NAME with $NUM_EPOCHS epochs..."
CUDA_VISIBLE_DEVICES=0 python run_glue.py \
--model_name_or_path google-bert/bert-base-cased \
--task_name $TASK_NAME \
--do_train \
--do_eval \
--max_seq_length 128 \
--per_device_train_batch_size 32 \
--learning_rate 2e-5 \
--num_train_epochs $NUM_EPOCHS \
--output_dir $LOG_DIR/$TASK_NAME/ \
--overwrite_output_dir
echo "Finished training for task: $TASK_NAME"
done
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