experiment_mini.sh

#!/bin/bash
python run.py \
    --lm_type bert-tiny \
    --run_name cpu-test-bert \
    --dataset_names ag_news SetFit/amazon_counterfactual_en \
    --num_subsamples 2 \
    --num_train 10 \
    --num_test 10 \
    --num_train_epochs_classification 1 \
    --num_train_epochs_pretrain 1 \
    --per_device_train_batch_size_pretrain 4 \
    --per_device_train_batch_size_classification 4 \
    --per_device_eval_batch_size_classification 4

python run.py \
    --lm_type gpt2-tiny \
    --run_name cpu-test-gpt2 \
    --dataset_names ag_news SetFit/amazon_counterfactual_en \
    --num_subsamples 2 \
    --num_train 10 \
    --num_test 10 \
    --num_train_epochs_classification 1 \
    --num_train_epochs_pretrain 1 \
    --per_device_train_batch_size_pretrain 4 \
    --per_device_train_batch_size_classification 4 \
    --per_device_eval_batch_size_classification 4

# python run.py \
#     --lm_type mistral-lora-zero-shot-tiny \
#     --run_name cpu-test-mistral-lora-zero-shot-tiny \
#     --dataset_names ag_news SetFit/amazon_counterfactual_en \
#     --num_subsamples 2 \
#     --num_train 10 \
#     --num_test 10 \
#     --num_train_epochs_classification 1 \
#     --num_train_epochs_pretrain 1 \
#     --per_device_train_batch_size_pretrain 4 \
#     --per_device_train_batch_size_classification 4 \
#     --per_device_eval_batch_size_classification 4